FolkloreDeterministic, rule-based variant interpretation platform for clinical genetics laboratories. Automates ACMG/AMP 2015 classification using a Bayesian point-based framework (Tavtigian et al. 2018) with BayesDel ClinGen SVI-calibrated thresholds (Pejaver et al. 2022). Integrates 8 reference databases (gnomAD v4.1, ClinVar, dbNSFP 4.9c, SpliceAI, gnomAD Constraint, HPO, ClinGen, Ensembl VEP). Analyzes nuclear and mtDNA variants, structural and copy-number variants (SV/CNV), with trio/family and cohort analysis. Supports HPO-based phenotype matching, biomedical literature mining across 2M+ PubMed publications, and structured clinical report generation. AI assists in evidence synthesis but does not make classification decisions. EU-hosted on dedicated infrastructure in Helsinki, Finland (GDPR-compliant).https://folklore.helena.bioFolklorebiotools:Folklore3.39.1RRID:SCR_028669rrid3.39.1Web applicationWeb APIhttp://edamontology.org/topic_3574Human geneticshttp://edamontology.org/topic_0625Genotype and phenotypehttp://edamontology.org/topic_3325Rare diseaseshttp://edamontology.org/topic_0199Genetic variationhttp://edamontology.org/topic_3063Medical informaticsLinuxPythonProprietaryMatureCommercialRestricted accesshttp://edamontology.org/operation_3225Variant classificationhttp://edamontology.org/data_3498Sequence variationshttp://edamontology.org/format_3016VCF

http://edamontology.org/data_2955Sequence report

http://edamontology.org/data_0920Genotype/phenotype report

http://edamontology.org/data_1622Disease report

http://edamontology.org/operation_3197Genetic variation analysishttp://edamontology.org/operation_0305Literature searchhttp://edamontology.org/operation_0362Genome annotationhttps://github.com/helena-bioinformatics/folklore-mcpRepositoryPublic Apache-2.0 MCP protocol adapter source; the Folklore SaaS platform and clinical interpretation backend remain proprietary.https://api.helena.bio/folklore/v1/mcpServicePublic remote endpoint for Folklore Clinical Variant Interpretation MCP version 1.2.2.https://registry.modelcontextprotocol.io/v0.1/servers?search=io.github.helena-bioinformatics%2Ffolklore&version=latestSoftware catalogueOfficial MCP Registry entry: io.github.helena-bioinformatics/folklore.https://folklore.helena.bio/integrationsOtherOfficial Folklore integrations and MCP client connection page.https://api.helena.bio/folklore/v1/healthTechnical monitoringPublic health and discovery metadata endpoint for the Folklore MCP service.https://github.com/helena-bioinformatics/folklore-mcpSource codeApache-2.0 standalone MCP protocol adapter. Excludes proprietary clinical interpretation logic, private data, credentials and operational infrastructure.1.2.2https://folklore.helena.bio/docsGeneralComplete production documentation covering every threshold, database version, and classification rule. Intended for clinical geneticists, laboratory directors, accreditation auditors, and bioinformaticians.https://folklore.helena.bio/how-it-worksGeneralSeven-stage analysis pipeline (quality control, annotation, classification, phenotype matching, literature, screening, interpretation) transforming a raw VCF into a clinician-ready report, each stage producing traceable, auditable output.https://folklore.helena.bio/methodologyGeneralACMG/AMP 2015 classification methodology (Richards et al. 2015) via Bayesian point-based system (Tavtigian et al. 2018), BayesDel ClinGen SVI-calibrated thresholds (Pejaver et al. 2022), and SpliceAI aligned to ClinGen SVI 2023 (Walker et al. 2023). Optional ClinGen VCEP overlay for ~50-60 genes. Strictly evidence-based, no ML determines pathogenicity.https://folklore.helena.bio/methodology/mtdnaGeneralMitochondrial DNA variant classification under the ClinGen Mitochondrial Disease Working Group (MMDWG) 2020 specification (McCormick et al. 2020). Operates as an independent module from the nuclear ACMG/AMP pipeline; every variant carries an explicit framework provenance label. Strength tiers follow ClinGen mtDNA VCEP v1.0.0.https://folklore.helena.bio/methodology/family-analysisGeneralInheritance-aware evidence from trio (proband + both parents), duo, and proband-plus-sibling analyses. Implements ClinGen SVI 2018 de novo PS2/PM6 (PMID 29543229), Jarvik & Browning 2016 LOD segregation framework (PMID 27236918), and ClinGen SVI 2021 PP1 strength bands. Augments the existing ACMG/AMP classification without re-calling variants.https://folklore.helena.bio/methodology/svGeneralStructural and copy-number variant evaluation under the Riggs 2020 joint ACMG/ClinGen technical standard. Documents the point-based loss and gain metrics, dosage-sensitivity evidence, and five-tier classification, with reference data and documented limitations.https://folklore.helena.bio/screening-methodologyGeneralPrioritizes classified variants for clinical review. After ACMG classification determines what each variant is, screening determines which to review first based on patient-specific clinical relevance. Evaluates seven independent dimensions, applies clinical profile boosts, and produces a four-tier priority ranking with transparent, visible score components.https://folklore.helena.bio/docs/folklore-connectorAPI documentationCanonical connector guide for Folklore Clinical Variant Interpretation MCP (io.github.helena-bioinformatics/folklore), version 1.2.2.https://github.com/helena-bioinformatics/folklore-mcp#readmeGeneralPublic Apache-2.0 MCP protocol adapter README. The Folklore SaaS platform and clinical interpretation backend remain proprietary.https://github.com/helena-bioinformatics/folklore-mcp/blob/main/CHANGELOG.mdRelease notesRelease history for the public Folklore MCP protocol adapter.10.5281/zenodo.21105027Preprint1.0Methodological framework for real-world performance studies of the platform's variant classification, demonstrated on three internal validation cohorts.10.5281/zenodo.21189571Preprint1.0A Deterministic Classification Core with an Agentic Interpretation Layer: An Architecture for Auditable, Human-Gated Clinical Variant Analysis10.5281/zenodo.21763096PreprintRobustness and cross-cohort concordance of developmental regulons in endometrial carcinoma. Authors: Draga Toncheva, Vasil Sgurev and Vladimir Mitev.10.5281/zenodo.21922952Other1.2.2Archived public Apache-2.0 Folklore MCP adapter release. All-version DOI: 10.5281/zenodo.21922951.10.5281/zenodo.22093164Other1.3.1Archived public Apache-2.0 Folklore MCP adapter release with four read-only tools, including semantic Literature Corpus search. All-version DOI: 10.5281/zenodo.21922951.10.3389/fgene.2026.1925492MethodMitev V. A methodological framework for real-world performance studies of clinical variant classification platforms at early organizational stages. Frontiers in Genetics 17:1925492, published 14 September 2026. Method demonstrated on 97 cases across three cohorts; independent validation remains future work.Helena Bioinformaticscontact@helena.biohttps://helena.bioInstituteDeveloperFolkloreDeterministic, rule-based variant interpretation platform for clinical genetics laboratories. Automates ACMG/AMP 2015 classification using a Bayesian point-based framework (Tavtigian et al. 2018) with BayesDel ClinGen SVI-calibrated thresholds (Pejaver et al. 2022). Integrates 8 reference databases (gnomAD v4.1, ClinVar, dbNSFP 4.9c, SpliceAI, gnomAD Constraint, HPO, ClinGen, Ensembl VEP). Analyzes nuclear and mtDNA variants, structural and copy-number variants (SV/CNV), with trio/family and cohort analysis. Supports HPO-based phenotype matching, biomedical literature mining across 2M+ PubMed publications, and structured clinical report generation. AI assists in evidence synthesis but does not make classification decisions. EU-hosted on dedicated infrastructure in Helsinki, Finland (GDPR-compliant).https://folklore.helena.bioHelixInsightbiotools:HelixInsight3.39.1RRID:SCR_028669rrid3.39.1Web APIWeb applicationhttp://edamontology.org/topic_3574Human geneticshttp://edamontology.org/topic_0625Genotype and phenotypehttp://edamontology.org/topic_3325Rare diseaseshttp://edamontology.org/topic_0199Genetic variationhttp://edamontology.org/topic_3063Medical informaticsLinuxPythonProprietaryMatureCommercialRestricted accesshttp://edamontology.org/operation_3225Variant classificationhttp://edamontology.org/data_3498Sequence variationshttp://edamontology.org/format_3016VCF

http://edamontology.org/data_2955Sequence report

http://edamontology.org/data_0920Genotype/phenotype report

http://edamontology.org/data_1622Disease report

http://edamontology.org/operation_3197Genetic variation analysishttp://edamontology.org/operation_0305Literature searchhttp://edamontology.org/operation_0362Genome annotationhttps://github.com/helena-bioinformatics/folklore-mcpRepositoryPublic Apache-2.0 MCP protocol adapter source; the Folklore SaaS platform and clinical interpretation backend remain proprietary.https://api.helena.bio/folklore/v1/mcpServicePublic remote endpoint for Folklore Clinical Variant Interpretation MCP version 1.2.2.https://registry.modelcontextprotocol.io/v0.1/servers?search=io.github.helena-bioinformatics%2Ffolklore&version=latestSoftware catalogueOfficial MCP Registry entry: io.github.helena-bioinformatics/folklore.https://folklore.helena.bio/integrationsOtherOfficial Folklore integrations and MCP client connection page.https://api.helena.bio/folklore/v1/healthTechnical monitoringPublic health and discovery metadata endpoint for the Folklore MCP service.https://github.com/helena-bioinformatics/folklore-mcpSource codeApache-2.0 standalone MCP protocol adapter. Excludes proprietary clinical interpretation logic, private data, credentials and operational infrastructure.1.2.2https://folklore.helena.bio/docsGeneralComplete production documentation covering every threshold, database version, and classification rule. Intended for clinical geneticists, laboratory directors, accreditation auditors, and bioinformaticians.https://folklore.helena.bio/how-it-worksGeneralSeven-stage analysis pipeline (quality control, annotation, classification, phenotype matching, literature, screening, interpretation) transforming a raw VCF into a clinician-ready report, each stage producing traceable, auditable output.https://folklore.helena.bio/methodologyGeneralACMG/AMP 2015 classification methodology (Richards et al. 2015) via Bayesian point-based system (Tavtigian et al. 2018), BayesDel ClinGen SVI-calibrated thresholds (Pejaver et al. 2022), and SpliceAI aligned to ClinGen SVI 2023 (Walker et al. 2023). Optional ClinGen VCEP overlay for ~50-60 genes. Strictly evidence-based, no ML determines pathogenicity.https://folklore.helena.bio/methodology/mtdnaGeneralMitochondrial DNA variant classification under the ClinGen Mitochondrial Disease Working Group (MMDWG) 2020 specification (McCormick et al. 2020). Operates as an independent module from the nuclear ACMG/AMP pipeline; every variant carries an explicit framework provenance label. Strength tiers follow ClinGen mtDNA VCEP v1.0.0.https://folklore.helena.bio/methodology/family-analysisGeneralInheritance-aware evidence from trio (proband + both parents), duo, and proband-plus-sibling analyses. Implements ClinGen SVI 2018 de novo PS2/PM6 (PMID 29543229), Jarvik & Browning 2016 LOD segregation framework (PMID 27236918), and ClinGen SVI 2021 PP1 strength bands. Augments the existing ACMG/AMP classification without re-calling variants.https://folklore.helena.bio/methodology/svGeneralStructural and copy-number variant evaluation under the Riggs 2020 joint ACMG/ClinGen technical standard. Documents the point-based loss and gain metrics, dosage-sensitivity evidence, and five-tier classification, with reference data and documented limitations.https://folklore.helena.bio/screening-methodologyGeneralPrioritizes classified variants for clinical review. After ACMG classification determines what each variant is, screening determines which to review first based on patient-specific clinical relevance. Evaluates seven independent dimensions, applies clinical profile boosts, and produces a four-tier priority ranking with transparent, visible score components.https://folklore.helena.bio/docs/folklore-connectorAPI documentationCanonical connector guide for Folklore Clinical Variant Interpretation MCP (io.github.helena-bioinformatics/folklore), version 1.2.2.https://github.com/helena-bioinformatics/folklore-mcp#readmeGeneralPublic Apache-2.0 MCP protocol adapter README. The Folklore SaaS platform and clinical interpretation backend remain proprietary.https://github.com/helena-bioinformatics/folklore-mcp/blob/main/CHANGELOG.mdRelease notesRelease history for the public Folklore MCP protocol adapter.10.5281/zenodo.21105027Preprint1.0Methodological framework for real-world performance studies of the platform's variant classification, demonstrated on three internal validation cohorts.10.5281/zenodo.21189571Preprint1.0A Deterministic Classification Core with an Agentic Interpretation Layer: An Architecture for Auditable, Human-Gated Clinical Variant Analysis10.5281/zenodo.21763096PreprintRobustness and cross-cohort concordance of developmental regulons in endometrial carcinoma. Authors: Draga Toncheva, Vasil Sgurev and Vladimir Mitev.10.5281/zenodo.21922952Other1.2.2Archived public Apache-2.0 Folklore MCP adapter release. All-version DOI: 10.5281/zenodo.21922951.10.5281/zenodo.22093164Other1.3.1Archived public Apache-2.0 Folklore MCP adapter release with four read-only tools, including semantic Literature Corpus search. All-version DOI: 10.5281/zenodo.21922951.Helena Bioinformaticscontact@helena.biohttps://helena.bioInstituteDeveloperNoodleNoodle is a public, read-only web application for semantic discovery and exploration of biomedical literature sourced from PubMed, Europe PMC, and OpenAlex. It accepts natural-language research questions and presents ranked publications together with gene, genetic variant, and phenotype views. Publication pages provide provenance, identifiers, source links, indexed concepts, and navigable semantic-neighbourhood graphs. The companion Noodle Biomedical Literature Discovery MCP exposes the same public discovery domain through a read-only, source-linked Model Context Protocol interface with bounded citation and semantic graph traversal. Semantic proximity, citation distance, co-mention, and search rank are discovery signals and do not establish scientific evidence, causality, diagnosis, or treatment.https://noodle.helena.bio/noodlebiotools:noodle0.2.0RRID:SCR_028920rridWeb APIWeb applicationhttp://edamontology.org/topic_0091BioinformaticsFreewareMatureFree of chargeOpen accesshttp://edamontology.org/operation_0305Literature searchSemantic retrieval and navigation of biomedical publications by research question, gene, variant, phenotype, and related-publication neighbourhood.https://www.helena.bio/OtherDeveloped and operated by Helena Bioinformatics.https://github.com/helena-bioinformatics/noodle-mcpRepositoryPublic Apache-2.0 source for the standalone Noodle Biomedical Literature Discovery MCP adapter.https://api.helena.bio/noodle/v1/mcpServicePublic read-only Streamable HTTP endpoint for Noodle Biomedical Literature Discovery MCP version 0.2.0.https://registry.modelcontextprotocol.io/v0/servers?search=io.github.helena-bioinformatics%2FnoodleSoftware catalogueOfficial MCP Registry entry: io.github.helena-bioinformatics/noodle.https://noodle.helena.bio/integrationsOtherOfficial Noodle integrations and MCP client connection page.https://api.helena.bio/noodle/v1/healthTechnical monitoringPublic health endpoint for the Noodle MCP service.https://github.com/helena-bioinformatics/noodle-mcpSource codeApache-2.0 standalone MCP protocol adapter. Excludes private corpus implementation, credentials, private data, and operational infrastructure.0.2.0https://noodle.helena.bio/methodologyGeneralPublic methodology, retrieval boundary, semantic-proximity limitations, and provenance policy.https://noodle.helena.bio/data-sourcesOtherAttributed biomedical literature sources, source roles, update boundaries, and correction handling.https://noodle.helena.bio/editorial-policyGovernanceEditorial, correction, attribution, and content-governance policy.https://noodle.helena.bio/mcpAPI documentationCanonical connector and agent-selection guide for Noodle Biomedical Literature Discovery MCP version 0.2.0.https://github.com/helena-bioinformatics/noodle-mcp#readmeGeneralPublic Apache-2.0 MCP adapter README, tool surface, graph boundary, and connection guidance.https://github.com/helena-bioinformatics/noodle-mcp/blob/main/CHANGELOG.mdRelease notesRelease history for the public Noodle MCP protocol adapter.HelixInsightuses10.5281/zenodo.221519901.0Public technical service description, methodology boundary, provenance, graph contract, and citation metadata for Noodle.10.5281/zenodo.22166486Other0.2.0Archived public Apache-2.0 Noodle Biomedical Literature Discovery MCP adapter release. All-version DOI: 10.5281/zenodo.22166485.Helena Bioinformaticscontact@helena.biohttps://www.helena.bio/InstitutePrimary contactDeveloperMaintainerProviderSupportPrimary developer, maintainer, service provider, and support contact for Noodle.BioExcel Building Blocks tutorials: Protein MD Setup tutorial through REST APIThis tutorial aims to illustrate the process of setting up a simulation system containing a protein, step by step, using the BioExcel Building Blocks (biobb) REST API. The particular example used is the Lysozyme protein (PDB code 1AKI).https://mmb.irbbarcelona.org/biobb/availability/tutorials/rest-apibioexcel_building_blocks_tutorials_protein_md_setup_tutorial_through_rest_apibiotools:bioexcel_building_blocks_tutorials_protein_md_setup_tutorial_through_rest_api1.0Web APIWorkflowhttp://edamontology.org/topic_0176Molecular dynamicshttp://edamontology.org/topic_0081Structure analysishttp://edamontology.org/topic_2814Protein structure analysisLinuxMacWindowsPythonApache-2.0BioExcelEmergingFree of chargeOpen accessToolsInteroperabilitySpainUKhttp://edamontology.org/operation_0477Protein modellinghttp://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_3872Topology datahttp://edamontology.org/format_3880GROMACS tophttp://edamontology.org/format_3883GROMACS itp

http://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3910trr

https://mmb.irbbarcelona.org/biobb/availability/tutorials/rest-apiOtherTutorial in HTMLhttps://biobb-wf-md-setup-api.readthedocs.io/en/latest/index.htmlOtherTutorial in Read the Docshttps://github.com/bioexcel/biobb_wf_md_setup_apiOtherSource Code in GitHubhttps://github.com/bioexcel/biobb_wf_md_setup_apiSource codeMarch 2020https://biobb-wf-md-setup-api.readthedocs.io/en/latest/index.htmlOtherBioExcel Building Blocks API Tutorial documentationhttp://mmb.irbbarcelona.org/biobb-api/restAPI documentationBioExcel Building Blocks Swagger API documentationbiobbusesgromacsuses10.1038/s41597-019-0177-431506435PMC6736963OtherBetaBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsGenís Bayarrigenis.bayarri@irbbarcelona.orgPersonDeveloperDocumentorPrimary contactMaintainerSupportBioExcel Building Blocks tutorials: ABC MD SetupThis BioExcel Building Blocks library (BioBB) workflow provides a pipeline to setup DNA structures for the Ascona B-DNA Consortium (ABC) members. It follows the work started with the NAFlex tool to offer a single, reproducible pipeline for structure preparation, ensuring reproducibility and coherence between all the members of the consortium.https://mmb.irbbarcelona.org/biobb/workflows/#abc-md-setupbioexcel_building_blocks_tutorials_abc_md_setupbiotools:bioexcel_building_blocks_tutorials_abc_md_setup1.0Workflowhttp://edamontology.org/topic_0176Molecular dynamicshttp://edamontology.org/topic_0097Nucleic acid structure analysisMacWindowsLinuxPythonApache-2.0BioExcelEmergingFree of chargeOpen accessInteroperabilityTools3D-BioInfoSpainUKhttp://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/operation_0477Protein modellinghttp://edamontology.org/data_3494DNA sequencehttp://edamontology.org/format_2330Textual format

http://edamontology.org/data_3872Topology datahttp://edamontology.org/format_3881AMBER top

http://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3878mdcrdhttp://edamontology.org/format_3650NetCDF

https://biobb-wf-amber-md-setup.readthedocs.io/en/latest/abcsetup_tutorial.htmlOtherTutorial in Read the Docshttps://github.com/bioexcel/biobb_wf_amber_md_setupRepositorySource code in GitHubhttps://github.com/bioexcel/biobb_wf_amber_md_setupSource codehttps://biobb-wf-amber-md-setup.readthedocs.io/en/latest/abcsetup_tutorial.htmlOtherWorkflow Documentation in Read the Docsbiobbusesambertoolsuses10.1038/s41597-019-0177-431506435PMC6736963OtherBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsBioExcel Center of Excellence for Computational Biomolecular Researchhttps://www.bioexcel.euConsortiumProviderAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactDeveloperDocumentorMaintainerGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonDeveloperDocumentorMaintainerBioExcel Building Blocks tutorials: Protein-Ligand Complex MD Setup (Amber Version)This tutorial aims to illustrate the process of setting up a simulation system containing a protein in complex with a ligand, step by step, using the BioExcel Building Blocks library (biobb) wrapping the AmberTools utility from the AMBER package. The particular example used is the T4 lysozyme protein (PDB code 3HTB) with two residue modifications L99A/M102Q complexed with the small ligand 2-propylphenol (3-letter code JZ4).https://mmb.irbbarcelona.org/biobb/workflows/#amber-protein-ligand-complex-md-setupbioexcel_building_blocks_tutorials_protein-ligand_complex_md_setup_amber_versionbiotools:bioexcel_building_blocks_tutorials_protein-ligand_complex_md_setup_amber_version1.0Workflowhttp://edamontology.org/topic_0176Molecular dynamicshttp://edamontology.org/topic_0081Structure analysishttp://edamontology.org/topic_2814Protein structure analysisMacWindowsLinuxPythonApache-2.0BioExcelEmergingFree of chargeOpen accessInteroperabilityTools3D-BioInfoSpainUKhttp://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/operation_0477Protein modellinghttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_3872Topology datahttp://edamontology.org/format_3881AMBER top

http://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3878mdcrdhttp://edamontology.org/format_3650NetCDF

https://biobb-wf-amber-md-setup.readthedocs.io/en/latest/mdsetup_lig_tutorial.htmlOtherTutorial in Read the Docshttps://github.com/bioexcel/biobb_wf_amber_md_setupRepositorySource Codehttps://github.com/bioexcel/biobb_wf_amber_md_setupSource codehttps://biobb-wf-amber-md-setup.readthedocs.io/en/latest/mdsetup_lig_tutorial.htmlOtherRead the Docs workflow documentationbiobbusesambertoolsuses10.1038/s41597-019-0177-431506435PMC6736963OtherBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsBioExcel Center of Excellence for Computational Biomolecular Researchhttps://www.bioexcel.euConsortiumProviderAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactDeveloperDocumentorMaintainerGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonDeveloperDocumentorMaintainerBioExcel Building Blocks tutorials: Structural DNA helical parameters from MD trajectoryThis tutorial aims to illustrate the process of extracting structural and dynamical properties from a DNA MD trajectory helical parameters, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the Drew Dickerson Dodecamer sequence -CGCGAATTCGCG- (PDB code 1BNA). The trajectory used is a 500ns-long MD simulation taken from the BigNASim database (NAFlex_DDD_II entry).https://mmb.irbbarcelona.org/biobb/workflows/#structural-dna-helical-parametersbioexcel_building_blocks_tutorials_structural_dna_helical_parameters_from_md_trajectorybiotools:bioexcel_building_blocks_tutorials_structural_dna_helical_parameters_from_md_trajectory1.0Workflowhttp://edamontology.org/topic_0097Nucleic acid structure analysisWindowsLinuxMacPythonApache-2.0BioExcelEmergingFree of chargeOpen accessInteroperabilityTools3D-BioInfoSpainUKhttp://edamontology.org/operation_0262Nucleic acid property calculationhttp://edamontology.org/operation_2481Nucleic acid structure analysishttp://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3650NetCDFhttp://edamontology.org/format_3878mdcrd

http://edamontology.org/data_3905Histogramhttp://edamontology.org/format_1637dat

http://edamontology.org/data_0912Nucleic acid propertyhttp://edamontology.org/format_1637dat

http://edamontology.org/data_2968Imagehttp://edamontology.org/format_3603PNG

https://biobb-wf-dna-helparms.readthedocs.io/en/latest/tutorial.htmlOtherTutorial in Read the Docshttps://github.com/bioexcel/biobb_wf_dna_helparmsRepositorySource code in GitHubhttps://github.com/bioexcel/biobb_wf_dna_helparmsSource codehttps://biobb-wf-dna-helparms.readthedocs.io/en/latest/tutorial.htmlOtherWorkflow documentation in Read the Docsbiobbusescurvesuses10.1038/s41597-019-0177-431506435PMC6736963OtherBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsBioExcel Center of Excellence for Computational Biomolecular Researchhttps://www.bioexcel.euConsortiumProviderAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactDeveloperDocumentorMaintainerGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonDeveloperDocumentorMaintainerBioExcel Building Blocks tutorials: AMBER Constant pH MD setupThis tutorial aims to illustrate the process of setting up a simulation system to run constant pH Molecular Dynamics simulations with AMBER, step by step, using the BioExcel Building Blocks library (biobb) wrapping the AmberTools utility from the AMBER package. The particular example used is the Bovine Pancreatic Trypsin Inhibitor (BPTI) protein (PDB code 6PTI).https://mmb.irbbarcelona.org/biobb/workflows/#amber-constant-ph-md-setupbioexcel_building_blocks_tutorials_amber_constant_ph_md_setupbiotools:bioexcel_building_blocks_tutorials_amber_constant_ph_md_setup1.0Workflowhttp://edamontology.org/topic_0176Molecular dynamicshttp://edamontology.org/topic_2814Protein structure analysisMacLinuxWindowsPythonApache-2.0BioExcelEmergingFree of chargeOpen accessInteroperabilityTools3D-BioInfoSpainUKhttp://edamontology.org/operation_0477Protein modellinghttp://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_3872Topology datahttp://edamontology.org/format_3881AMBER top

http://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3878mdcrdhttp://edamontology.org/format_3650NetCDF

https://biobb-wf-amber-md-setup.readthedocs.io/en/latest/mdsetup_ph_tutorial.htmlOtherTutorial in Read the Docshttps://github.com/bioexcel/biobb_wf_amber_md_setupRepositorySource Code in GitHubhttps://github.com/bioexcel/biobb_wf_amber_md_setupSource codehttps://biobb-wf-amber-md-setup.readthedocs.io/en/latest/mdsetup_ph_tutorial.htmlOtherRead the Docs workflow documentationbiobbusesambertoolsuses10.1038/s41597-019-0177-431506435PMC6736963OtherBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsBioExcel Center of Excellence for Computational Biomolecular Researchhttps://www.bioexcel.euConsortiumProviderAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactDeveloperDocumentorMaintainerGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonDeveloperDocumentorMaintainerBioExcel Building Blocks tutorials: Protein MD Setup (Amber Version)This tutorial aims to illustrate the process of setting up a simulation system containing a protein, step by step, using the BioExcel Building Blocks library (biobb) wrapping the AmberTools utility from the AMBER package. The particular example used is the Lysozyme protein (PDB code 1AKI).https://mmb.irbbarcelona.org/biobb/workflows/#amber-protein-md-setupbioexcel_building_blocks_tutorials_protein_md_setup_amber_versionbiotools:bioexcel_building_blocks_tutorials_protein_md_setup_amber_version1.0Workflowhttp://edamontology.org/topic_0176Molecular dynamicshttp://edamontology.org/topic_0081Structure analysishttp://edamontology.org/topic_2814Protein structure analysishttp://edamontology.org/topic_0092Data visualisationWindowsLinuxMacPythonApache-2.0BioExcelEmergingFree of chargeOpen accessToolsInteroperabilitySpainhttp://edamontology.org/operation_2406Protein structure analysishttp://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/operation_0570Structure visualisationhttp://edamontology.org/operation_3890Trajectory visualizationhttp://edamontology.org/operation_0477Protein modellinghttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_3872Topology datahttp://edamontology.org/format_3881AMBER top

http://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3650NetCDFhttp://edamontology.org/format_3878mdcrd

https://biobb-wf-amber-md-setup.readthedocs.io/en/latest/mdsetup_tutorial.htmlOtherTutorial in Read the Docshttps://github.com/bioexcel/biobb_wf_amber_md_setupRepositorySource Code in GitHubhttps://github.com/bioexcel/biobb_wf_amber_md_setupSource codehttps://biobb-wf-amber-md-setup.readthedocs.io/en/latest/mdsetup_tutorial.htmlOtherRead the Docs Workflow Documentationambertoolsusesbiobbuses10.1038/s41597-019-0177-431506435PMC6736963OtherBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsBioExcel Center of Excellence for Computational Biomolecular Researchhttps://www.bioexcel.euConsortiumProviderAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactDeveloperDocumentorMaintainerGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonDeveloperDocumentorMaintainerBioExcel Building Blocks tutorials: Macromolecular Coarse-Grained FlexibilityThis tutorial aims to illustrate the process of generating protein conformational ensembles from 3D structures using Coarse-Grained tools from the FlexServ server and analysing its molecular flexibilityhttps://mmb.irbbarcelona.org/biobb/workflows/#macromolecular-coarse-grained-flexibilitybioexcel_building_blocks_tutorials_macromolecular_coarse-grained_flexibilitybiotools:bioexcel_building_blocks_tutorials_macromolecular_coarse-grained_flexibility1.0Workflowhttp://edamontology.org/topic_3892Biomolecular simulationhttp://edamontology.org/topic_0081Structure analysishttp://edamontology.org/topic_0160Sequence sites, features and motifshttp://edamontology.org/topic_0082Structure predictionhttp://edamontology.org/topic_0092Data visualisationWindowsLinuxMacPythonApache-2.0BioExcelEmergingFree of chargeOpen accessToolsInteroperabilitySpainUKhttp://edamontology.org/operation_2406Protein structure analysishttp://edamontology.org/operation_0474Protein structure predictionhttp://edamontology.org/operation_2939Principal component visualisationhttp://edamontology.org/operation_0250Protein property calculationhttp://edamontology.org/operation_3890Trajectory visualizationhttp://edamontology.org/operation_3891Essential dynamicshttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3874PCAziphttp://edamontology.org/format_3464JSONhttp://edamontology.org/format_1476PDB

https://mmb.irbbarcelona.org/biobb/workflows#macromolecular-coarse-grained-flexibilityOtherMain web site (BioBB Workflows)https://biobb-wf-flexserv.readthedocs.io/en/latest/index.htmlOtherTutorial in Read The Docshttps://github.com/bioexcel/biobb_wf_flexservRepositorySource Code in GitHubhttps://github.com/bioexcel/biobb_wf_flexservSource code1.0https://biobb-wf-flexserv.readthedocs.io/en/latest/index.htmlOtherRead The Docs workflow documentationbiobbusesflexservusesnglviewusespcasuiteuses10.1038/s41597-019-0177-431506435PMC6736963OtherBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactDeveloperDocumentorMaintainerGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/es/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonContributorDeveloperMaintainerBioExcel CoEhttps://bioexcel.eu/ConsortiumProviderBioExcel Building Blocks tutorials: Protein-Ligand Complex MD Setup (Gromacs Version)This tutorial aims to illustrate the process of setting up a simulation system containing a protein in complex with a ligand, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the T4 lysozyme L99A/M102Q protein (PDB code 3HTB), in complex with the 2-propylphenol small molecule (3-letter Code JZ4).http://mmb.irbbarcelona.org/biobb/workflows/#gromacs-protein-ligand-complex-md-setupbioexcel_building_blocks_tutorials_protein-ligand_complex_md_setupbiotools:bioexcel_building_blocks_tutorials_protein-ligand_complex_md_setup1.0Workflowhttp://edamontology.org/topic_0176Molecular dynamicshttp://edamontology.org/topic_2814Protein structure analysishttp://edamontology.org/topic_0128Protein interactionsMacLinuxWindowsPythonApache-2.0BioExcelEmergingFree of chargeOpen accessToolsInteroperabilitySpainUKhttp://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/operation_2480Structure analysishttp://edamontology.org/operation_2406Protein structure analysishttp://edamontology.org/data_1461Protein-ligand complexhttp://edamontology.org/format_1476PDB

http://edamontology.org/data_3872Topology datahttp://edamontology.org/format_3880GROMACS tophttp://edamontology.org/format_3883GROMACS itp

http://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3910trr

https://biobb-wf-protein-complex-md-setup.readthedocs.io/en/latest/index.htmlOtherTutorial in Read the Docshttps://github.com/bioexcel/biobb_wf_protein-complex_md_setupRepositorySource code in GitHubhttps://github.com/bioexcel/biobb_wf_protein-complex_md_setupSource codeMarch 2020https://biobb-wf-protein-complex-md-setup.readthedocs.io/en/latest/index.htmlOtherRead the Docs workflow documentationbiobbusesgromacsusesopen_babelusesacpypeuses10.1038/s41597-019-0177-431506435PMC6736963OtherBetaBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/profile/genis-bayarriPersonDeveloperDocumentorMaintainerAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/profile/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactPau Andriopau.andrio@bsc.eshttps://www.bsc.es/andrio-balado-pauPersonDeveloperDocumentorMaintainerSupportBioExcel Centre of Excellencehttps://bioexcel.eu/ConsortiumProviderBioExcel Building Blocks tutorials: Mutation Free Energy CalculationsThis tutorial aims to illustrate how to compute a fast-growth mutation free energy calculation, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the Staphylococcal nuclease protein (PDB code 1STN), a small, minimal protein, appropriate for a short tutorial.http://mmb.irbbarcelona.org/biobb/workflows/#mutation-free-energy-calculationsbioexcel_building_blocks_tutorials_mutation_free_energy_calculationsbiotools:bioexcel_building_blocks_tutorials_mutation_free_energy_calculations1.0Workflowhttp://edamontology.org/topic_0176Molecular dynamicshttp://edamontology.org/topic_3120Protein variantsMacLinuxWindowsPythonApache-2.0BioExcelEmergingFree of chargeOpen accessToolsInteroperabilitySpainUKhttp://edamontology.org/operation_0331Variant effect predictionhttp://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/operation_2406Protein structure analysishttp://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3875XTChttp://edamontology.org/data_3872Topology datahttp://edamontology.org/format_3880GROMACS tophttp://edamontology.org/format_3883GROMACS itp

http://edamontology.org/data_3779Annotated texthttp://edamontology.org/format_2330Textual format

http://edamontology.org/data_3905Histogramhttp://edamontology.org/format_3603PNG

http://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3910trr

https://biobb-wf-pmx-tutorial.readthedocs.io/en/latest/index.htmlOtherTutorial in Read the Docshttps://github.com/bioexcel/biobb_wf_pmx_tutorialOtherSource code in GitHubhttps://github.com/bioexcel/biobb_wf_pmx_tutorialSource codeMarch 2020https://biobb-wf-pmx-tutorial.readthedocs.io/en/latest/index.htmlOtherRead the Docs workflow documentationbiobbusesgromacsusespmxuses10.1038/s41597-019-0177-431506435PMC6736963OtherBetaBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/profile/genis-bayarriPersonDeveloperDocumentorMaintainerAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/profile/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactPau Andriopau.andrio@bsc.eshttps://www.bsc.es/andrio-balado-pauPersonDeveloperDocumentorMaintainerSupportBioExcel Centre of Excellencehttps://bioexcel.eu/ConsortiumProviderBioExcel Building Blocks tutorials: Automatic Ligand parameterizationThis tutorial aims to illustrate the process of ligand parameterization for a small molecule, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the Ibuprofen small compound (3-letter code IBP, Drugbank code DB01050), a non-steroidal anti-inflammatory drug (NSAID) derived from propionic acid.http://mmb.irbbarcelona.org/biobb/workflows/#automatic-ligand-parameterizationbioexcel_building_blocks_tutorials_automatic_ligand_parameterizationbiotools:bioexcel_building_blocks_tutorials_automatic_ligand_parameterization1.0Workflowhttp://edamontology.org/topic_0154Small moleculeshttp://edamontology.org/topic_0176Molecular dynamicsLinuxMacWindowsPythonApache-2.0BioExcelEmergingFree of chargeOpen accessToolsInteroperabilitySpainUKhttp://edamontology.org/operation_2426Modelling and simulationhttp://edamontology.org/data_1463Small molecule structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_3872Topology datahttp://edamontology.org/format_3880GROMACS tophttp://edamontology.org/format_3883GROMACS itp

https://biobb-wf-ligand-parameterization.readthedocs.io/en/latest/index.htmlOtherTutorial in Read the Docshttps://github.com/bioexcel/biobb_wf_ligand_parameterizationRepositorySource Code in GitHubhttps://github.com/bioexcel/biobb_wf_ligand_parameterizationSource codeMarch 2020https://biobb-wf-ligand-parameterization.readthedocs.io/en/latest/index.htmlOtherRead the Docs workflow documentationbiobbusesacpypeusesopen_babeluses10.1038/s41597-019-0177-431506435PMC6736963OtherBeta10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/profile/genis-bayarriPersonDeveloperDocumentorMaintainerAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/profile/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactPau Andriopau.andrio@bsc.eshttps://www.bsc.es/andrio-balado-pauPersonDeveloperDocumentorMaintainerSupportBioExcel Centre of Excellencehttps://bioexcel.eu/ConsortiumProviderBioExcel Building Blocks tutorials: Protein-ligand DockingThis tutorial aims to illustrate the process of protein-ligand docking, step by step, using the BioExcel Building Blocks library (biobb).https://mmb.irbbarcelona.org/biobb/workflows/#protein-ligand-docking-(fpocket)bioexcel_building_blocks_tutorials_protein-ligand_dockingbiotools:bioexcel_building_blocks_tutorials_protein-ligand_docking1.0Workflowhttp://edamontology.org/topic_2275Molecular modellinghttp://edamontology.org/topic_0082Structure predictionhttp://edamontology.org/topic_0092Data visualisationMacWindowsLinuxPythonApache-2.0BioExcelEmergingFree of chargeOpen accessInteroperabilityToolsSpainUKhttp://edamontology.org/operation_0482Protein-ligand dockinghttp://edamontology.org/operation_0570Structure visualisationhttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_1463Small molecule structurehttp://edamontology.org/format_3814SDFhttp://edamontology.org/format_1476PDB

http://edamontology.org/data_1461Protein-ligand complexhttp://edamontology.org/format_1476PDB

https://biobb-wf-virtual-screening.readthedocs.io/en/latest/cluster_bs_tutorial.htmlOtherTutorial in Read The Docs (PDB Cluster90 Binding Site Version)https://github.com/bioexcel/biobb_wf_virtual-screeningRepositorySource Code in GitHubhttps://biobb-wf-virtual-screening.readthedocs.io/en/latest/ebi_api_tutorial.htmlOtherTutorial in Read the Docs (PDBe REST-API Binding Site Version)https://biobb-wf-virtual-screening.readthedocs.io/en/latest/fpocket_tutorial.htmlOtherTutorial in Read the Docs (Fpocket Binding Site Version)https://github.com/bioexcel/biobb_wf_virtual-screeningSource code1.0https://biobb-wf-virtual-screening.readthedocs.io/en/latest/cluster_bs_tutorial.htmlOtherRead the Docs Workflow Documentation (PDB Cluster90 Binding Site Version)https://biobb-wf-virtual-screening.readthedocs.io/en/latest/ebi_api_tutorial.htmlOtherRead the Docs Workflow Documentation (PDBe REST-API Binding Site Version)https://biobb-wf-virtual-screening.readthedocs.io/en/latest/fpocket_tutorial.htmlOtherRead the Docs Workflow Documentation (Fpocket Binding Site Version)biobbusesautodock_vinausesfpocketusespdbeuses10.1038/s41597-019-0177-431506435PMC6736963Other10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsBioExcel Center of Excellence for Computational Biomolecular Researchhttps://www.bioexcel.euConsortiumProviderGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonDeveloperDocumentorMaintainerAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactBioExcel Building Blocks tutorials: Molecular Structure CheckingThis tutorial aims to illustrate the process of checking a molecular structure before using it as an input for a Molecular Dynamics simulation, step by step, using the BioExcel Building Blocks (biobb).https://mmb.irbbarcelona.org/biobb/workflows/#molecular-structure-checkingbioexcel_building_blocks_tutorials_molecular_structure_checkingbiotools:bioexcel_building_blocks_tutorials_molecular_structure_checking1.0Workflowhttp://edamontology.org/topic_3892Biomolecular simulationhttp://edamontology.org/topic_0081Structure analysishttp://edamontology.org/topic_2814Protein structure analysishttp://edamontology.org/topic_0082Structure predictionhttp://edamontology.org/topic_0092Data visualisationMacLinuxWindowsPythonApache-2.0BioExcelEmergingFree of chargeOpen accessToolsInteroperabilitySpainUKhttp://edamontology.org/operation_2426Modelling and simulationhttp://edamontology.org/operation_0570Structure visualisationhttp://edamontology.org/operation_0477Protein modellinghttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_2048Reporthttp://edamontology.org/format_3464JSON

https://biobb-wf-structure-checking.readthedocs.io/en/latest/index.htmlOtherTutorial in Read the Docshttps://github.com/bioexcel/biobb_wf_structure_checkingRepositorySource Code in GitHubhttps://github.com/bioexcel/biobb_wf_structure_checkingSource codeSource Code in GitHubhttps://biobb-wf-structure-checking.readthedocs.io/en/latest/index.htmlOtherDocumentation in Read the Docsbiobbuses10.1038/s41597-019-0177-431506435PMC6736963OtherBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactDeveloperDocumentorMaintainerGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/es/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonContributorDeveloperMaintainerJosep Lluís Gelpígelpi@ub.eduhttps://www.bsc.es/es/gelpi-josephttps://orcid.org/0000-0002-0566-7723PersonDeveloperMaintainerSupportBioExcel CoEhttps://bioexcel.eu/ConsortiumProviderBioExcel Building Blocks tutorials: Molecular Interaction PotentialsThis tutorial aims to illustrate the process of computing classical molecular interaction potentials from protein structures step by step, using the BioExcel Building Blocks library (biobb)https://mmb.irbbarcelona.org/biobb/workflows/#molecular-interaction-potentialsbioexcel_building_blocks_tutorials_molecular_interaction_potentialsbiotools:bioexcel_building_blocks_tutorials_molecular_interaction_potentials1.0Workflowhttp://edamontology.org/topic_3892Biomolecular simulationhttp://edamontology.org/topic_0128Protein interactionshttp://edamontology.org/topic_0092Data visualisationLinuxMacWindowsPythonApache-2.0BioExcelEmergingFree of chargeOpen accessToolsInteroperabilitySpainUKhttp://edamontology.org/operation_0248Residue interaction calculationhttp://edamontology.org/operation_0272Residue contact predictionhttp://edamontology.org/operation_2480Structure analysishttp://edamontology.org/operation_2949Protein-protein interaction analysishttp://edamontology.org/operation_0570Structure visualisationhttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_1476PDB

http://edamontology.org/data_0906Protein interaction datahttp://edamontology.org/format_2330Textual format

http://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_1277Protein featureshttp://edamontology.org/format_2330Textual format

https://biobb-wf-cmip.readthedocs.io/en/latest/index.htmlOtherTutorial in Read The Docshttps://github.com/bioexcel/biobb_wf_cmipRepositorySource Code in GitHubhttps://github.com/bioexcel/biobb_wf_cmipSource code1.0https://biobb-wf-cmip.readthedocs.io/en/latest/index.htmlOtherRead the Docs workflow documentationbiobbusesnglviewusesclassical_molecular_interaction_potentials_cmipuses10.1038/s41597-019-0177-431506435PMC6736963OtherBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactDeveloperDocumentorMaintainerGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/es/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonContributorDeveloperMaintainerBioExcel CoEhttps://bioexcel.eu/ConsortiumProviderBioExcel Building Blocks tutorials: Protein MD Setup (Gromacs Version)This tutorial aims to illustrate the process of setting up a simulation system containing a protein, step by step, using the BioExcel Building Blocks library (biobb). The particular example used is the Lysozyme protein (PDB code 1AKI).http://mmb.irbbarcelona.org/biobb/workflows/#gromacs-protein-md-setupbioexcel_building_blocks_tutorials_protein_md_setupbiotools:bioexcel_building_blocks_tutorials_protein_md_setup1.0Workflowhttp://edamontology.org/topic_0176Molecular dynamicshttp://edamontology.org/topic_0081Structure analysishttp://edamontology.org/topic_2814Protein structure analysisMacWindowsLinuxPythonApache-2.0BioExcelEmergingFree of chargeOpen accessInteroperabilityToolsSpainUKhttp://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/operation_0477Protein modellinghttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_3872Topology datahttp://edamontology.org/format_3883GROMACS itphttp://edamontology.org/format_3880GROMACS top

http://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3910trr

https://biobb-wf-md-setup.readthedocs.io/en/latest/index.htmlOtherTutorial in Read the Docshttps://github.com/bioexcel/biobb_wf_md_setupRepositorySource code in GitHubhttps://github.com/bioexcel/biobb_wf_md_setupSource codehttps://biobb-wf-md-setup.readthedocs.io/en/latest/?badge=latestOtherRead the Docs workflow documentationbiobbusesgromacsuses10.1038/s41597-019-0177-431506435PMC6736963OtherBetaBioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/profile/genis-bayarriPersonDeveloperDocumentorMaintainerAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/profile/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactBioExcel Centre of Excellencehttps://bioexcel.eu/ConsortiumProviderPau Andriopau.andrio@bsc.eshttps://www.bsc.es/andrio-balado-pauPersonDeveloperDocumentorSupportBioExcel Building Blocks tutorials: Protein-Protein DockingThis tutorial aims to illustrate the process of protein-protein docking, step by step, using HADDOCK3 and the BioExcel Building Blocks (biobb)https://mmb.irbbarcelona.org/biobb/workflows/#protein-protein-dockingbioexcel_building_blocks_tutorials_protein-protein_dockingbiotools:bioexcel_building_blocks_tutorials_protein-protein_docking1.0Workflowhttp://edamontology.org/topic_2275Molecular modellingWindowsLinuxMacPythonApache-2.0BioExcelEmergingFree of chargeOpen accessInteroperabilityTools3D-BioInfoSpainhttp://edamontology.org/operation_2423Prediction and recognitionhttp://edamontology.org/operation_0478Molecular dockinghttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_2884Plot

https://github.com/bioexcel/biobb_wf_haddockRepositorySource Code in GitHubhttps://github.com/bioexcel/biobb_wf_haddockSource codeSource Code1.0https://github.com/bioexcel/biobb_workflows/tree/main/biobb_wf_haddock/dockerContainer fileDocker Container1.0https://github.com/bioexcel/biobb_wf_haddockGeneralInstallation instructionsWorkflow Documentationbiobbuseshaddock3usesnglviewuses10.1038/s41597-019-0177-431506435PMC6736963Primary1.0BioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonMaintainerRubén Chavesruben.chaves@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/ruben-chaveshttps://orcid.org/0009-0005-6656-2991PersonDeveloperDocumentorMaintainerBioExcel Building Blocks tutorials: Protein-Membrane MD analysisThis tutorial aims to illustrate the process of analyzing a membrane molecular dynamics (MD) simulation, step by step, using the BioExcel Building Blocks (biobb)https://mmb.irbbarcelona.org/biobb/workflows/#protein-membrane-md-analysisbioexcel_building_blocks_tutorials_protein-membrane_md_analysisbiotools:bioexcel_building_blocks_tutorials_protein-membrane_md_analysis1.0Workflowhttp://edamontology.org/topic_3892Biomolecular simulationhttp://edamontology.org/topic_0820Membrane and lipoproteinshttp://edamontology.org/topic_2814Protein structure analysisMacWindowsLinuxPythonApache-2.0BioExcelEmergingFree of chargeOpen accessInteroperabilityTools3D-BioInfoSpainhttp://edamontology.org/operation_2241Transmembrane protein visualisationhttp://edamontology.org/operation_0250Protein property calculationhttp://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/operation_0270Transmembrane protein analysishttp://edamontology.org/data_3872Topology datahttp://edamontology.org/format_3881AMBER tophttp://edamontology.org/format_3882PSFhttp://edamontology.org/format_1476PDBhttp://edamontology.org/format_3880GROMACS tophttp://edamontology.org/data_3870Trajectory datahttp://edamontology.org/format_3875XTChttp://edamontology.org/format_1476PDBhttp://edamontology.org/format_3650NetCDF

http://edamontology.org/data_0897Protein property

http://edamontology.org/data_2884Plot

http://edamontology.org/data_1277Protein features

https://github.com/bioexcel/biobb_wf_memRepositorySource Code in GitHubhttps://github.com/bioexcel/biobb_wf_memSource codeSource Code1.0https://github.com/bioexcel/biobb_workflows/tree/main/biobb_wf_mem/dockerContainer fileDocker Container1.0https://github.com/bioexcel/biobb_workflows/tree/main/biobb_wf_mem/cwlTool wrapper (CWL)CWL Specification1.0https://github.com/bioexcel/biobb_wf_memGeneralInstallation instructionsWorkflow Documentationbiobbusesnglviewusesmdanalysisuses10.1038/s41597-019-0177-431506435PMC6736963Primary1.0BioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC11189206Usage1.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonMaintainerRubén Chavesruben.chaves@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/ruben-chaveshttps://orcid.org/0009-0005-6656-2991PersonDeveloperDocumentorMaintainerBioExcel Building Blocks tutorials: AutoEncoders for Anomaly DetectionThis tutorial involves the use of a multilayer AutoEncoder (AE) for feature extraction and pattern recognition by analyzing Molecular Dynamic Simulations, step by step, using the BioExcel Building Blocks library (biobb)https://mmb.irbbarcelona.org/biobb/workflows/#autoencoders-for-anomaly-detectionbioexcel_building_blocks_tutorials_autoencoders_for_anomaly_detectionbiotools:bioexcel_building_blocks_tutorials_autoencoders_for_anomaly_detection1.0Workflowhttp://edamontology.org/topic_3892Biomolecular simulationhttp://edamontology.org/topic_3510Protein sites, features and motifshttp://edamontology.org/topic_3474Machine learningMacWindowsLinuxPythonApache-2.0BioExcelEmergingFree of chargeOpen accessInteroperabilityTools3D-BioInfoSpainhttp://edamontology.org/operation_3890Trajectory visualizationhttp://edamontology.org/operation_3092Protein feature detectionhttp://edamontology.org/operation_0250Protein property calculationhttp://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/data_3870Trajectory datahttp://edamontology.org/data_3872Topology data

http://edamontology.org/data_3842Molecular simulation datahttp://edamontology.org/format_3875XTChttp://edamontology.org/format_1476PDB

http://edamontology.org/data_2884Plothttp://edamontology.org/format_2330Textual format

https://github.com/bioexcel/biobb_wf_autoencoderRepositorySource Code in GitHubhttps://github.com/bioexcel/biobb_wf_autoencoderSource codeSource Code1.0https://github.com/bioexcel/biobb_workflows/tree/main/biobb_wf_autoencoder/dockerContainer fileDocker Container1.0https://github.com/bioexcel/biobb_workflows/tree/main/biobb_wf_autoencoder/cwlTool wrapper (CWL)CWL specification1.0https://github.com/bioexcel/biobb_wf_autoencoderGeneralInstallation instructionsWorkflow Documentationbiobbusesnglviewusespytorchusesmdtrajusesmatplotlibusesnumpyuses10.1038/s41597-019-0177-431506435PMC6736963Primary1.0BioExcel Building Blocks (BioBB)10.1371/journal.pcbi.101217338900779PMC111892061.0Using interactive Jupyter Notebooks and BioConda for FAIR and reproducible biomolecular simulation workflowsAdam Hospitaladam.hospital@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/adam-hospitalhttps://orcid.org/0000-0002-8291-8071PersonPrimary contactGenís Bayarrigenis.bayarri@irbbarcelona.orghttps://www.irbbarcelona.org/en/research/genis-bayarrihttps://orcid.org/0000-0003-0513-0288PersonMaintainerDeveloperPieter Zanderspieter.zanders@bsc.eshttps://www.bsc.es/zanders-marxuach-pieterhttps://orcid.org/0009-0000-3463-6806PersonDeveloperDocumentorMaintainercompareMS2compareMS2 is a tool for comparing sets of (tandem) mass spectra for clustering samples, molecular phylogenetics, identification of biological species or tissues, and quality control. compareMS2 currently consumes Mascot Generic Format, or MGF, and produces output in a variety of common image and distance matrix formats.https://github.com/524D/compareMS2comparems2biotools:comparems21.02.02.2Desktop applicationCommand-line toolhttp://edamontology.org/topic_0084Phylogenyhttp://edamontology.org/topic_0121Proteomicshttp://edamontology.org/topic_3172Metabolomicshttp://edamontology.org/topic_3520Proteomics experimentMacLinuxWindowsJavaScriptGoCMITProteomicsms-utilsMatureFree of chargeProteomicsNetherlandshttp://edamontology.org/operation_0567Phylogenetic tree visualisationhttp://edamontology.org/operation_2424Comparisonhttp://edamontology.org/data_2536Mass spectrometry datahttp://edamontology.org/format_3651MGF

http://edamontology.org/data_3272Species treehttp://edamontology.org/format_3603PNGhttp://edamontology.org/format_3604SVG

http://edamontology.org/data_2855Distance matrixhttp://edamontology.org/format_1912Nexus formathttp://edamontology.org/format_1991megahttp://edamontology.org/format_1910newick

https://github.com/524D/compareMS2Repositoryhttps://www.ms-utils.org/compareMS2.htmlSoftware cataloguehttps://research-software-directory.org/software/comparems2Software cataloguehttp://www.ms-utils.org/compareMS2.cSource code1.0http://www.ms-utils.org/compareMS2.htmlBinaries1.0http://www.ms-utils.org/compareMS2.cSource code1.0https://github.com/524D/compareMS2/tree/main/srcSource code2.0https://github.com/524D/compareMS2/tree/mainBinaries2.0http://www.ms-utils.org/compareMS2.htmlGeneralCommand-line optionshttps://github.com/524D/compareMS2GeneralUser manualCommand-line optionsInstallation instructions10.1002/rcm.616222368051Primary1.010.1021/acs.jproteome.2c0045736173614PMC9903320Primary2.010.1021/acs.jproteome.1c0052834523928PMC8491155Review2.0lumc.nlhttps://www.lumc.nlInstituteSupportMagnus Palmbladmagnus.palmblad@gmail.comhttps://github.com/magnuspalmbladhttp://orcid.org/0000-0002-5865-8994PersonDeveloperPrimary contactDocumentorRob Marissenhttps://github.com/524Dhttps://orcid.org/0000-0002-1220-9173PersonDeveloperplantiSMASHPlantiSMASH is a specialized extension of antiSMASH for the identification and analysis of biosynthetic gene clusters (BGCs) in plant genomes. It supports advanced plant-specific detection rules and features for comparative genomics, visualization, and more.https://plantismash.bioinformatics.nl/plantismashbiotools:plantismash2.0-beta4http://edamontology.org/topic_0749Transcription factors and regulatory siteshttp://edamontology.org/topic_3473Data mininghttp://edamontology.org/topic_0085Functional genomicsMacWindowsLinuxAGPL-3.0https://github.com/plantismash/plantismash/releasesSoftware package2.0-beta4https://plantismash.github.io/documentation/General10.1093/nar/gkx305PMC55701731.010.1016/j.jmb.2026.16979841962628Primary2.0plantiSMASH 2.0: Improvements to Detection, Annotation, and Prioritization of Plant Biosynthetic Gene ClustersWEBnmaWEBnm@ provides quick, automated computation and analysis of low-frequency normal modes for protein structures.http://apps.cbu.uib.no/webnmawebnmabiotools:webnma3.5Web APISuitehttp://edamontology.org/topic_2814Protein structure analysishttp://edamontology.org/topic_0736Protein folds and structural domainsLinuxWindowsMacPythonGPL-3.0BiB toolsCBU toolsUiB toolsELIXIR-NOELIXIR-NorwayMatureFree of chargeOpen access3D-BioInfoNorwayhttp://edamontology.org/operation_0570Structure visualisationhttp://edamontology.org/operation_0244Protein flexibility and motion analysishttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_2884Plothttp://edamontology.org/format_3508PDF

http://edamontology.org/data_1354Sequence profilehttp://edamontology.org/format_2330Textual format

Constructs elastic network model from alpha carbon coordinates of the protein, and computes properties to describe large scale conformations. Computes normal modes, fluctuation profiles, inter-residue correlations, conformational overlap analysis and vector field representations. Structural amino acid profiles, and normal mode characteristics describing protein motion, visualized in plots and decorated structure visualizations. White space delimited tabular data for normal modes and the provided plotshttp://edamontology.org/operation_2487Protein structure comparisonhttp://edamontology.org/operation_0337Visualisationhttp://edamontology.org/data_0886Structure alignmenthttp://edamontology.org/format_2200FASTA-like (text)http://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_2884Plothttp://edamontology.org/format_3508PDF

http://edamontology.org/data_0889Structural profilehttp://edamontology.org/format_2330Textual format

Performs comparative analysis of the normal modes of protein structures. Computes the Bhattacharyya Coefficient (BC) and the Root Mean Squared Inner Product (RMSIP) of aligned parts of the proteins. Alignment of sets of proteins to be compared. Multiple protein structures Heatmaps, dendrograms and structural amino acid profiles for visual comparison of structural similarity. White space delimited tabular data for the provided plotshttps://github.com/reuter-group/webnma3RepositoryIssue trackerhttps://elixir.no/helpdeskHelpdeskHelpdesk and support for ELIXIR Norway services.http://apps.cbu.uib.no/webnma3/howto/singleQuick start guidehttp://apps.cbu.uib.no/webnma3/qandaFAQhttp://apps.cbu.uib.no/webnma3/aboutGeneralCitation instructionsnumpyusesbiopythonusesmatplotlibusesmustangusesdsspuses10.1186/s12859-014-0427-625547242PMC4339738Primary2.010.1186/1471-2105-6-5215762993PMC1274249Primary1.0Nathalie ReuterNathalie.Reuter@uib.nohttp://www.cbu.uib.no/reuter/https://orcid.org/0000-0002-3649-7675PersonPrimary contactDeveloperSandhya P Tiwarihttps://orcid.org/0000-0002-0747-3826PersonDeveloperKidane M TeklePersonDeveloperTristan CragnoliniPersonDeveloperSvenn H GrindhaugPersonDeveloperLars SkjærvenPersonDeveloperGisle SalensmindePersonDeveloperEdvin FuglebakkPersonDeveloperSiv M HollupPersonDeveloperDepartment of Molecular Biology, University of Bergen, NorwayInstituteProviderComputational Biology Unit, Department of Informatics, University of Bergen, NorwayInstituteProviderUiBInstituteProviderProfilerProfiler is a peer-reviewed, open-source web platform and desktop version for end-to-end multi-omics data analysis, integrating statistical methods, machine learning, and artificial intelligence into a unified workflow. The platform supports proteomics, metabolomics, lipidomics, transcriptomics, genomics, and other omics datasets from raw or tabular inputs. Profiler provides automated preprocessing, data exploration, biomarker discovery, AI-driven modeling, survival analysis, and biological interpretation using enrichment analysis. Designed for both bioinformaticians and experimental scientists, Profiler enables reproducible, explainable, and high-performance omics analysis through an intuitive web interface. Profiler is developed by the PRISM U1192 laboratory and protected by INSERM Transfer.https://prism-profiler.univ-lille.fr/profilerbiotools:profiler1.0doi:10.1093/bioinformatics/btaf644doi1.0Desktop applicationWeb applicationWorkflowhttp://edamontology.org/topic_3316Computer scienceMacLinuxWindowsOtherMatureFree of chargeOpen accessToolsTrainingInteroperabilityMetabolomicsProteomicsRare DiseasesFrancehttps://prism-profiler.univ-lille.fr/Othersofteware linkhttps://github.com/yanisZirem/Profiler_v1_requests_datatestsRepositorydataset exampleshttps://github.com/yanisZirem/prism-profilerRepositoryDesktop versionhttps://doi.org/10.5281/zenodo.17478158Source codehttps://github.com/yanisZirem/Profiler_v1_requests_datatestsTest data1.0https://prism-profiler.univ-lille.fr/app/Software packagehttps://prism-profiler.univ-lille.fr/citation/Citation instructions10.1093/bioinformatics/btaf64441324558Primary1.0Michel Salzetmichel.salzet@univ-lille.frhttps://www.laboratoire-prism.fr/member/michel-salzet/https://orcid.org/0000-0003-4318-0817PersonProfessor Michel Salzet known for his work in immunology, oncology and proteomicASAFindASAFind is a software that predicts the intracellular location of proteins in cells with four membrane-bound complex plastids of red algal origin. These plastids evolved via eukaryote-eukaryote endosymbiosis and for example can be found in diatoms and cryptophytes. ASAFind uses protein sequence data and external predictions of signal peptides (by the tools SignalP and TargetP), and predicts plastid proteins, and proteins that are targeted to the periplastidic compartment from these data; optionally, a graphical output can generated.https://asafind.jcu.cz/asafindbiotools:asafind2.0ScriptCommand-line toolWeb servicehttp://edamontology.org/topic_2229Cell biologyhttp://edamontology.org/topic_0078Proteinshttp://edamontology.org/topic_0780Plant biologyhttp://edamontology.org/topic_0622GenomicsMacLinuxPythonCC-BY-SA-4.0ELIXIR-CZCzech RepublicMatureFree of chargeOpen accessToolsPlant SciencesMarine MetagenomicsMicrobial BiotechnologyCzech Republichttp://edamontology.org/operation_2489Subcellular localisation predictionhttp://edamontology.org/operation_0239Sequence motif recognitionhttp://edamontology.org/operation_0422Protein cleavage site predictionhttp://edamontology.org/data_2886Protein sequence recordhttp://edamontology.org/format_1929FASTAhttp://edamontology.org/data_1270Feature table

http://edamontology.org/data_1277Protein features

http://edamontology.org/data_2884Plot

https://asafind.jcu.czServiceWeb Servicehttps://github.com/ASAFind/ASAFind-2RepositoryInformation and source code, for local installation or developmenthttps://asafind.jcu.cz/download-page/Downloads pageDownload page on web-service, links to repository2.0https://asafind.jcu.cz/download-page/Installation instructionssignalpusestargetpuses10.1111/tpj.7013840464854PMC12136025Primary2.0Publication of the current version of ASAFind (2.0)10.1111/tpj.1273425438865PMC4329603Other1.0Publication of the first version of ASAFind10.48550/arXiv.2303.02509Benchmarking study1.0Benchmarking of the performance of the first version of ASAFindMarta Vohnoutovámvohnoutova@jcu.czhttps://www.jcu.cz/cz/univerzita/lide/clovek?identita=Vohnoutova_Marta_61699https://orcid.org/0000-0002-8915-8626PersonContributorDeveloperMaintainerAnsgar Gruberagruber@prf.jcu.czhttps://www.jcu.cz/cz/univerzita/lide/clovek?identita=Gruber_Ansgar_118401https://orcid.org/0000-0002-5876-4391PersonPrimary contactDeveloperDocumentorseqfuA collection of utilities to manipulate FASTA and FASTQ files, supporting Gzipped input.https://telatin.github.io/seqfu2/seqfubiotools:seqfu1.10.01.11.01.12.01.13.01.14.01.15.01.16.01.17.01.19.01.20.01.21.01.22.01.22.3Command-line toolhttp://edamontology.org/topic_0077Nucleic acidshttp://edamontology.org/topic_0080Sequence analysishttp://edamontology.org/operation_2478Nucleic acid sequence analysishttp://edamontology.org/data_2044Sequence

http://edamontology.org/data_2977Nucleic acid sequence

seqfu [subcommand] FASTX > FASTXhttps://telatin.github.io/seqfu2OtherDocumentationhttps://github.com/telatin/seqfu2/Repositoryhttps://github.com/telatin/seqfu2Software packagehttps://github.com/telatin/seqfu2/releasesDownloads pagehttps://bioconda.github.io/recipes/seqfu/README.htmlSoftware package1.0.0-1.22.3https://telatin.github.io/seqfu2/User manual10.3390/bioengineering805005934066939PMC8148589Primary1.0MS AnnikaMS Annika is a crosslink search engine based on MS Amanda, aimed at identifying crosslinks of cleavable and non-cleavable crosslinkers from MS2 and MS3 spectra. It can deal with a wide variety of cross-linkers and provides robust and transparent FDR control based on a target-decoy approach. MS Annika is available free of charge as a plug-in for Proteome Discoverer.https://github.com/hgb-bin-proteomics/MSAnnikams_annikabiotools:ms_annikaProteome Discoverer 3.2: MS Annika 3.0 v3.0.7Proteome Discoverer 3.1: MS Annika 3.0 v3.0.7Proteome Discoverer 3.0: MS Annika 2.0 v1.1.4fixProteome Discoverer 2.5: MS Annika 2.0 v1.1.3Proteome Discoverer 2.4: MS Annika v1.0.0Proteome Discoverer 2.3: MS Annika v1.0.0Plug-inhttp://edamontology.org/topic_0130Protein folding, stability and designhttp://edamontology.org/topic_0736Protein folds and structural domainshttp://edamontology.org/topic_0128Protein interactionshttp://edamontology.org/topic_0121Proteomicshttp://edamontology.org/topic_0091BioinformaticsWindowsC#FreewareMatureFree of chargeOpen accesshttp://edamontology.org/operation_3631Peptide identificationhttp://edamontology.org/operation_3646Peptide database searchhttp://edamontology.org/operation_3755PTM localisationhttp://edamontology.org/operation_3645PTM identificationhttp://edamontology.org/operation_3649Target-Decoyhttp://edamontology.org/data_0943Mass spectrumhttp://edamontology.org/format_3651MGFhttp://edamontology.org/format_3712Thermo RAWhttp://edamontology.org/data_2886Protein sequence recordhttp://edamontology.org/format_1929FASTA

http://edamontology.org/data_0857Sequence search resultshttp://edamontology.org/format_2330Textual format

https://github.com/hgb-bin-proteomics/MSAnnikaRepositoryMS Annika version archivehttps://github.com/hgb-bin-proteomics/MSAnnika/raw/master/releases/latest/PD3.2/latest.zipSoftware packageLatest MS Annika version for Proteome Disoverer 3.2PD3.2:latesthttps://github.com/hgb-bin-proteomics/MSAnnika/raw/master/releases/latest/PD3.1/latest.zipSoftware packageLatest MS Annika version for Proteome Disoverer 3.1PD3.1:latesthttps://github.com/hgb-bin-proteomics/MSAnnika/raw/master/releases/latest/PD3.0/latest.zipSoftware packageLatest MS Annika version for Proteome Disoverer 3.0PD3.0:latesthttps://github.com/hgb-bin-proteomics/MSAnnika/raw/master/releases/latest/PD2.5/latest.zipSoftware packageLatest MS Annika version for Proteome Disoverer 2.5PD2.5:latesthttps://hgb-bin-proteomics.github.io/MSAnnika/Generalhttps://github.com/hgb-bin-proteomics/MSAnnika/raw/master/MS_Annika_3.0_UserManual.pdfUser manualhttps://github.com/hgb-bin-proteomics/MSAnnika/raw/master/tutorial/MS_Annika_3.0_Tutorial.pdfTraining materialDetailed tutorial how to use MS Annikahttps://www.youtube.com/watch?v=L1lVt35PYv4Training materialDetailed tutorial how to use MS Annikams_amandauses10.1021/acs.jproteome.0c0100033852321PMC8155564Primary1.0MS Annika for cleavable crosslink identification from MS2 spectra10.1021/acs.jproteome.3c0032537566781PMC10476269Primary2.0MS Annika 2.0 for cleavable crosslink identification from MS3 spectra10.1038/s42004-024-01386-x39702463PMC11659399Primary3.0MS Annika 3.0 for non-cleavable crosslink identificationViktoria Dorferviktoria.dorfer@fh-hagenberg.athttp://bioinformatics.fh-hagenberg.at/https://orcid.org/0000-0002-5332-5701PersonPrimary contactMicha Birklbauermicha.birklbauer@fh-hagenberg.athttp://bioinformatics.fh-hagenberg.at/https://orcid.org/0009-0005-1051-179XPersonDeveloperViVo PlatformViVo Platform is a free, open-access web application for the analysis of in vivo tumor growth data in mouse models. Designed to standardize in vivo efficacy analysis, improve research reproducibility, and reduce animal usage, it provides tools to upload tumor volume or bioluminescence imaging (BLI) datasets, configure analysis parameters, detect outliers, and automatically compute tumor growth rates (TGR), group comparisons, and reports. By standardizing data processing and incorporating advanced temporal modeling, ViVo Platform enhances statistical power and contributes to the 3Rs principle by reducing the number of animals needed in preclinical efficacy studies.https://gcanudo-barreras.github.io/ViVo-Platform/vivo_platformbiotools:vivo_platformResearch Beta 1.0Web applicationhttp://edamontology.org/topic_3379Preclinical and clinical studieshttp://edamontology.org/topic_2640Oncologyhttp://edamontology.org/topic_3386Laboratory animal sciencehttp://edamontology.org/topic_0091BioinformaticsJavaScriptMITEmergingFree of chargeOpen accesshttp://edamontology.org/operation_2945Data analysishttp://edamontology.org/operation_2238Statistical calculationhttp://edamontology.org/operation_2426Modelling and simulationhttp://edamontology.org/data_3722Physiology parameterhttp://edamontology.org/format_3752CSVhttp://edamontology.org/data_3723Morphology parameterhttp://edamontology.org/format_3752CSV

http://edamontology.org/data_2048Reporthttp://edamontology.org/format_2331HTMLhttp://edamontology.org/format_3603PNGhttp://edamontology.org/format_3752CSV

http://edamontology.org/operation_2409Data handlinghttp://edamontology.org/operation_0337Visualisationhttps://gcanudo-barreras.github.io/ViVo-Platform/Servicehttps://www.biorxiv.org/content/10.1101/2025.10.14.682266v1OtherbioRxiv preprinthttps://github.com/gcanudo-barreras/ViVo-PlatformRepositoryhttps://github.com/gcanudo-barreras/ViVo-Platform/blob/main/README.mdGeneralhttps://github.com/gcanudo-barreras/ViVo-Platform/blob/main/ViVo_USER_MANUAL.mdUser manualhttps://www.biorxiv.org/content/10.1101/2025.10.14.682266v1OtherFull methodologyhttps://github.com/gcanudo-barreras/ViVo-Platform/releases/tag/v1.0-betaRelease notes10.1101/2025.10.14.682266MethodResearch Beta 1.0Guillermo Canudo-Barrerascanudobarreras@unizar.eshttps://orcid.org/0000-0002-1949-9185PersonDeveloperPrimary contactMaintainerSupportResearcher at Spanish National Research Council (CSIC). Developer.Eduardo Romanoseromanos.iacs@aragon.eshttps://orcid.org/0000-0002-9918-3374PersonContributorResearcher at Biomedical Research Center of Aragon (CIBA).Raquel P. Herreraraquelph@unizar.eshttps://orcid.org/0000-0002-5244-9569PersonContributorSenior scientist at Spanish National Research Council (CSIC).M. Concepción Gimenogimeno@unizar.eshttps://orcid.org/0000-0003-0553-0695PersonContributorFull professor at Spanish National Research Council (CSIC).MaCPepDB - Mass Centric Peptide DatabaseA Database to Quickly Access All Tryptic Peptides of the UniProtKBhttps://macpepdb.cubimed.rub.de/macpepdb_-_mass_centric_peptide_databasebiotools:macpepdb_-_mass_centric_peptide_database3.0.0Database portalhttp://edamontology.org/topic_0121ProteomicsRustJavaScriptOtherCUBiMed.RUBBioInfra.ProtMatureFree of chargeOpen accessGermanyhttps://github.com/medbioinf/macpepdbRepositoryBackend implementation written in Rust / Axumhttps://github.com/medbioinf/macpepdb-frontendRepositoryFrontend implementation written in Rust / Dioxushttps://docs.rs/macpepdb/latest/macpepdb/web/index.htmlAPI documentation10.1021/acs.jproteome.0c0096733724838Primary1.0Julian Uszkoreithttp://orcid.org/0000-0001-7522-4007Dirk Winkelhardtdirk.winkelhardt@rub.dehttps://orcid.org/0000-0001-8770-2221PD Dr. Martin Eisenacherhttps://orcid.org/0000-0003-2687-7444MirGeneDBMirGeneDB is a database of manually curated microRNA genes that have been validated and annotated as initially described in Fromm et al. 2015 , Fromm et al. 2020 and Fromm et al 2022. MirGeneDB 3.0 (Clarke and Hoye et al. 2024 ) includes more than 21,000 microRNA gene entries representing more than 1,700 microRNA families from 114 metazoan species. All microRNAs can be browsed, searched and downloaded.http://mirgenedb.org/mirgenbiotools:mirgen3.0doi:10.25504/FAIRsharing.QXSgvFdoi2.0Database portalhttp://edamontology.org/topic_0659Functional, regulatory and non-coding RNAhttp://edamontology.org/topic_0204Gene regulationhttp://edamontology.org/topic_3299Evolutionary biologyhttp://edamontology.org/topic_3500Zoologyhttp://edamontology.org/topic_2815Human biologyLinuxWindowsMacCC0-1.0UiO toolsELIXIR-NOELIXIR-NorwayMatureFree of chargeOpen accessNorwayhttp://edamontology.org/operation_2422Data retrievalhttp://edamontology.org/operation_0564Sequence visualisationhttp://edamontology.org/data_1097Sequence accession (nucleic acid)http://edamontology.org/format_1929FASTAhttp://edamontology.org/data_1869Organism identifier

http://edamontology.org/data_3134Gene transcript reporthttp://edamontology.org/format_2331HTML

http://edamontology.org/data_0880RNA secondary structurehttp://edamontology.org/format_2331HTML

Data retrieval: curated miRNA. Organism identifier: a specific miRNA identifier or a species for all miRNAs for that species. Gene transcript report: with metadata and visualization. RNA secondary structure: the hairpin loop of the miRNA with bases.http://edamontology.org/operation_0224Query and retrievalhttp://edamontology.org/data_1097Sequence accession (nucleic acid)

http://edamontology.org/data_3495RNA sequencehttp://edamontology.org/format_1929FASTA

http://edamontology.org/data_2012Sequence coordinateshttp://edamontology.org/format_2305GFFhttp://edamontology.org/format_3003BED

http://edamontology.org/data_3917Count matrixhttp://edamontology.org/format_2330Textual format

https://elixir.no/helpdeskHelpdeskhttps://www.mirgenedb.org/downloadBiological dataSequence downloads for 75 species3.0https://www.mirgenedb.org/informationGeneral10.1093/nar/gkab110134850127PMC8728216Primary2.110.1093/nar/gkz88531598695PMC6943042Primary2.010.1146/annurev-genet-120213-09202326473382PMC4743252Primary1.010.1093/nar/gkae109439673268PMC11701709Primary3.0Bastian FrommBastianFromm@gmail.comhttps://orcid.org/0000-0003-0352-3037PersonPrimary contactDeveloperMaintainerSupportKevin J. Petersonkevin.j.peterson@dartmouth.eduPersonDeveloperMaintainerThe Norwegian Bioinformatics Platform (ELIXIR-Norway) Helpdesksupport@elixir.nohttps://elixir.no/helpdeskConsortiumSupportUniversity of Oslohttps://www.uio.no/english/index.htmlgrid.5510.101xtthb5610.13039/501100005366InstituteProviderDeepSigPrediction of secretory signal peptides in protein sequenceshttps://busca.biocomp.unibo.it/deepsig/deepsigbiotools:deepsig1.2.5Web applicationCommand-line toolhttp://edamontology.org/topic_3307Computational biologyhttp://edamontology.org/topic_3510Protein sites, features and motifshttp://edamontology.org/topic_0123Protein propertiesLinuxWindowsMacPythonC++GPL-3.0Bologna Biocomputing GroupMatureFree of chargeOpen accessItalyhttp://edamontology.org/operation_0418Protein signal peptide detectionhttp://edamontology.org/data_2974Protein sequence (raw)http://edamontology.org/format_1929FASTAhttp://edamontology.org/data_3028Taxonomyhttp://edamontology.org/format_2330Textual format

http://edamontology.org/data_0896Protein reporthttp://edamontology.org/format_2331HTML

https://github.com/BolognaBiocomp/deepsigSource code1.2.5https://hub.docker.com/r/bolognabiocomp/deepsigContainer file1.2.5https://github.com/BolognaBiocomp/deepsigCommand-line options10.1093/bioinformatics/btx81829280997PMC5946842Primary1.0ELIXIR-ITA-BOLOGNAhttp://biocomp.unibo.itInstituteProviderCastrense Savojardocastrense.savojardo2@unibo.ithttps://orcid.org/0000-0002-7359-0633PersonDeveloperPrimary contactPier Luigi Martellipierluigi.martelli@unibo.ithttp://biocomp.unibo.ithttps://orcid.org/0000-0002-0274-5669PersonPrimary contactMuGVREThe MuG Virtual Research Environment is an analysis platform for 3D/4D genomics analyses. It integrates genomics tools for chromatin dynamics data.https://www.multiscalegenomics.eu/mugvrebiotools:mugvre1.0Web applicationWorkbenchhttp://edamontology.org/topic_3176DNA packaginghttp://edamontology.org/topic_3169ChIP-seqhttp://edamontology.org/topic_0097Nucleic acid structure analysishttp://edamontology.org/topic_2275Molecular modellingPHPPythonApache-2.0RIS3CAT VEISFree of chargeOpen accesshttp://edamontology.org/operation_0292Sequence alignmenthttp://edamontology.org/operation_3198Read mappinghttp://edamontology.org/data_2044Sequencehttp://edamontology.org/format_1930FASTQhttp://edamontology.org/format_1929FASTAhttp://edamontology.org/data_3210Genome index

http://edamontology.org/data_0863Sequence alignmenthttp://edamontology.org/format_2572BAM

http://edamontology.org/operation_0475Nucleic acid structure predictionhttp://edamontology.org/operation_2426Modelling and simulationhttp://edamontology.org/operation_0279Nucleic acid folding analysishttp://edamontology.org/data_2977Nucleic acid sequencehttp://edamontology.org/format_2200FASTA-like (text)http://edamontology.org/data_1255Sequence featureshttp://edamontology.org/format_2305GFF

http://edamontology.org/data_3870Trajectory data

http://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/operation_0478Molecular dockinghttp://edamontology.org/operation_3900DNA-binding protein predictionhttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_2877Protein complexhttp://edamontology.org/format_1476PDB

http://edamontology.org/operation_3222Peak callinghttp://edamontology.org/operation_1781Gene regulatory network analysishttp://edamontology.org/data_0905Protein interaction raw datahttp://edamontology.org/format_2572BAM

http://edamontology.org/data_1276Nucleic acid featureshttp://edamontology.org/format_3003BED

http://edamontology.org/operation_3927Network analysishttp://edamontology.org/operation_0279Nucleic acid folding analysishttp://edamontology.org/data_0905Protein interaction raw datahttp://edamontology.org/format_1930FASTQ

http://edamontology.org/data_3872Topology datahttp://edamontology.org/format_4002pickle

http://edamontology.org/data_0906Protein interaction datahttp://edamontology.org/format_4002pickle

http://edamontology.org/operation_2478Nucleic acid sequence analysishttp://edamontology.org/data_1461Protein-ligand complexhttp://edamontology.org/format_1476PDB

http://edamontology.org/data_2084Nucleic acid report

http://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/operation_2481Nucleic acid structure analysishttp://edamontology.org/data_0883Structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_3870Trajectory data

http://edamontology.org/operation_0432Nucleosome position predictionhttp://edamontology.org/operation_3454Phasinghttp://edamontology.org/data_0905Protein interaction raw datahttp://edamontology.org/format_2572BAM

http://edamontology.org/data_3002Annotation trackhttp://edamontology.org/format_2305GFF

http://edamontology.org/operation_0337Visualisationhttp://edamontology.org/operation_0570Structure visualisationhttp://edamontology.org/operation_0564Sequence visualisationhttp://edamontology.org/operation_3925Network visualisationhttp://edamontology.org/data_2012Sequence coordinateshttp://edamontology.org/data_3002Annotation trackhttp://edamontology.org/data_3869Simulationhttp://edamontology.org/data_0883Structurehttp://vre.multiscalegenomics.euServicehttps://github.com/Multiscale-Genomics/VRERepositoryhttps://www.multiscalegenomics.eu/MuGVRE/terms-of-use/Terms of usehttp://vre.multiscalegenomics.eu/help/starting.phpQuick start guidehttps://www.multiscalegenomics.eu/MuGVRE/training/Training materialnucleosome_dynamicsincludestadbitincludesjbrowseincludesnglincludes10.1101/602474Primary1.0Laia Codólaia.codo@bsc.eshttps://orcid.org/0000-0002-6797-8746PersonPrimary contactJosep Lluís Gelpíhttp://orcid.org/0000-0002-0566-7723PersonContributorMultiscale Complex Genomics Communityvre@multiscalegenomics.euhttps://www.multiscalegenomics.eu/ConsortiumDeveloperARTEMISa method for topology-independent superposition of RNA 3D structures and structure-based sequence alignmenthttps://github.com/david-bogdan-r/ARTEMISartemis3Dbiotools:artemis3Dversion 1.51Command-line toolScripthttp://edamontology.org/topic_3307Computational biologyhttp://edamontology.org/topic_0077Nucleic acidshttp://edamontology.org/topic_0097Nucleic acid structure analysishttp://edamontology.org/topic_0102Mappinghttp://edamontology.org/topic_3511Nucleic acid sites, features and motifshttp://edamontology.org/topic_0654DNAhttp://edamontology.org/topic_0099RNAMacLinuxWindowsPythonApache-2.03D-BioInfo-Structure-FunctionMatureFree of chargeOpen accesshttp://edamontology.org/operation_0503Pairwise structure alignmenthttp://edamontology.org/operation_2518Nucleic acid structure comparisonhttp://edamontology.org/data_1459Nucleic acid structurehttp://edamontology.org/format_1477mmCIFhttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_1459Nucleic acid structurehttp://edamontology.org/format_1477mmCIFhttp://edamontology.org/format_1476PDB

http://edamontology.org/data_1482Nucleic acid structure alignmenthttp://edamontology.org/format_2330Textual format

http://edamontology.org/data_0888Structure similarity scorehttp://edamontology.org/format_2330Textual format

http://edamontology.org/data_1459Nucleic acid structurehttp://edamontology.org/format_1477mmCIFhttp://edamontology.org/format_1476PDB

python3 artemis.py r=FILENAME q=FILENAME [OPTIONS]https://github.com/david-bogdan-r/ARTEMISRepositoryhttps://github.com/david-bogdan-r/ARTEMISSource codeversion 1.5https://github.com/david-bogdan-r/ARTEMIS/blob/main/README.mdQuick start guideREADME filehttps://github.com/david-bogdan-r/ARTEMIS/blob/main/ARTEMIS_TUTORIAL_v1.51.pdfUser manualTutorial in pdfartemuses10.1093/nar/gkae75839258540PMC11472068Primaryversion 1.510.1101/2024.04.06.588371version 1.0Davyd Bohdanhttps://orcid.org/0000-0002-6456-6658Janusz Bujnickihttps://orcid.org/0000-0002-6633-165XEugene Baulinhttps://orcid.org/0000-0003-4694-9783ChannelsDB 2.0A comprehensive resource of channels, pores and tunnels found in biomacromolecular structures deposited in the Protein Data Bank.https://channelsdb2.biodata.ceitec.cz/channelsdbbiotools:channelsdb2.0Database portalhttp://edamontology.org/topic_1317Structural biologyhttp://edamontology.org/topic_3306Biophysicshttp://edamontology.org/topic_0123Protein propertieshttp://edamontology.org/topic_0128Protein interactionshttp://edamontology.org/topic_0821Enzymeshttp://edamontology.org/topic_0820Membrane and lipoproteinshttp://edamontology.org/topic_0078Proteinshttp://edamontology.org/topic_0154Small moleculeshttp://edamontology.org/topic_3068Literature and languageLinuxWindowsMacJavaScriptC#FreewareLCC NCBRELIXIR-CZMatureFree of chargeOpen accessData3D-BioInfoCzech Republichttp://edamontology.org/operation_3431Data depositionhttp://edamontology.org/operation_0570Structure visualisationhttp://edamontology.org/operation_0250Protein property calculationhttp://edamontology.org/operation_0245Protein structural motif recognitionhttp://edamontology.org/data_3021UniProt accessionhttp://edamontology.org/format_2330Textual formathttp://edamontology.org/data_1127PDB IDhttp://edamontology.org/format_1477mmCIFhttp://edamontology.org/format_1476PDB

http://edamontology.org/data_2080Database search resultshttp://edamontology.org/format_3464JSONhttp://edamontology.org/format_2331HTMLhttp://edamontology.org/format_1476PDB

http://edamontology.org/data_2878Protein structural motifhttp://edamontology.org/format_2332XMLhttp://edamontology.org/format_3464JSON

https://channelsdb2.biodata.ceitec.czServicehttps://channelsdb2.biodata.ceitec.cz/documentation.htmlUser manualQuick start guideDatabase content Channels nomenclature MOLE settings List of cofactors used for channel determination. Description how to read the resuls page. How to access content of the database programatically.https://channelsdb2.biodata.ceitec.cz/methods.htmlGeneralFAQInfo about methodologyhttps://channelsdb2.biodata.ceitec.cz/about.htmlCitation instructionsContributions policyhttps://channelsdb2.biodata.ceitec.cz/apiAPI documentationmoleusescaverusesmoleonline_2.0usescaver_webuses10.1093/nar/gkx868Method1.010.1093/nar/gkad1012Primary2.0Lukáš Pravdaxpravda@ncbr.muni.czhttps://orcid.org/0000-0002-6435-4719PersonDeveloperDavid Sehnaldavid.sehnal@mail.muni.czhttps://orcid.org/0000-0002-0682-3089PersonDeveloperKarel Berkakarel.berka@upol.czhttps://orcid.org/0000-0001-9472-2589PersonPrimary contactContributorRadka Svobodováradka.svobodova@ceitec.muni.czhttps://orcid.org/0000-0002-3840-8760PersonContributorProviderDavid Bednář222755@mail.muni.czhttps://orcid.org/0000-0002-6803-0340PersonContributorPalacky University Olomouchttps://www.upol.cz/en/InstituteMasaryk University Brnohttps://www.muni.cz/enInstituteVáclav Bazgiervaclav.bazgier@upol.czhttps://orcid.org/0000-0003-3393-3010PersonDocumentorContributorAnna Špačkováanna.spackova@upol.czhttps://orcid.org/0000-0001-7142-3092PersonContributorDocumentorOndřej Vávravavra@enantis.comhttps://orcid.org/0000-0003-1396-2543PersonContributorTomáš Raček324965@mail.muni.czhttps://orcid.org/0000-0002-0296-2452PersonDeveloperMaintainerJiří Damborskýjiri@chemi.muni.czhttps://orcid.org/0000-0002-7848-8216PersonContributorPROTEOFORMERProteogenomic pipeline integrating ribosome profiling (RIBO-seq) data in the search for new proteoforms in proteomic validation data. The pipeline does a genome-wide construction of candidate translation products based on ribosome occupancy.https://github.com/Biobix/proteoformerproteoformerbiotools:proteoformer1.02.0Command-line toolhttp://edamontology.org/topic_0121Proteomicshttp://edamontology.org/topic_3120Protein variantshttp://edamontology.org/topic_3308TranscriptomicsLinuxMacRPerlSQLPythonGPL-3.0BIG N2NProteomicsBioBixUGentMatureFree of chargeOpen accesshttp://edamontology.org/operation_2423Prediction and recognitionhttp://edamontology.org/operation_3563RNA-seq read count analysishttp://edamontology.org/operation_3225Variant classificationhttp://edamontology.org/operation_0362Genome annotationhttp://edamontology.org/operation_2284Nucleic acid density plottinghttp://edamontology.org/operation_3198Read mappinghttp://edamontology.org/operation_3182Genome alignmenthttp://edamontology.org/operation_3800RNA-Seq quantificationhttp://edamontology.org/operation_3661SNP annotationhttp://edamontology.org/data_3496RNA sequence (raw)http://edamontology.org/format_1930FASTQ

http://edamontology.org/data_2080Database search resultshttp://edamontology.org/format_3621SQLite format

http://edamontology.org/data_2886Protein sequence recordhttp://edamontology.org/format_1929FASTA

perl mapping.pl --helphttps://github.com/Biobix/proteoformerRepositoryGitHub tool repo (PROTEOFORMER version 2.0)http://galaxy.ugent.be/Galaxy serviceGalaxy service of PROTEOFORMER version 1.0 (the Galaxy service of PROTEOFORMER version 2.0 is under way)http://www.biobix.be/research/downloads/proteoformer/OtherExplanation of the tool on the lab's websitehttps://github.com/Biobix/proteoformerSource codeGitHub repo2.0https://github.com/Biobix/proteoformer/tree/master/Galaxy%20filesTool wrapper (Galaxy)Galaxy wrapper files1.0https://github.com/Biobix/proteoformer/blob/master/README.mdUser manualFull elaborate documentation on usage and installation with lots of examples. Main documentation source.https://github.com/Biobix/proteoformer/blob/master/LICENSETerms of useGPU 3.0 license10.1093/nar/gku128325510491PMC4357689Primary1.010.1074/mcp.ra118.00121831040227PMC6692777Primary2.0Steven VerbruggenSteven.Verbruggen@UGent.behttps://orcid.org/0000-0001-9441-9539PersonPrimary contactDeveloperDocumentorMaintainerMain developer of the 2.0 versionGerben MenschaertGerben.Menschaert@ugent.behttps://orcid.org/0000-0002-7575-2085PersonPrimary contactContributorPI of this projectJeroen Crappéhttps://orcid.org/0000-0003-1677-9533PersonDeveloperMain developer of the 1.0 versionElvis NdahPersonDeveloperMain developer of the 1.0 versionSandra SteyaertPersonContributorContributor to the 1.0 versionAlexander KochPersonContributorContributor to the 1.0 versionGhent Universityhttps://www.ugent.be/enInstituteBioBixhttp://www.biobix.be/DivisionEBprotPerseus plugin for differential protein abundance analysis of labeling-based and label-free quantitative proteomics datahttps://github.com/cssblab/EBprotebprotbiotools:ebprot2.0Plug-inhttp://edamontology.org/topic_0121ProteomicsWindowsC++Apache-2.0ProteomicsMatureFree of chargeOpen accesshttp://edamontology.org/operation_3634Label-free quantificationhttp://edamontology.org/operation_3635Labeled quantificationhttp://edamontology.org/data_0945Peptide identificationhttps://github.com/cssblab/EBprotRepositoryhttps://github.com/cssblab/EBprot/issuesIssue trackerhttps://github.com/cssblab/EBprot/releasesSoftware packagehttps://github.com/cssblab/EBprot/wikiUser manual10.1021/acs.jproteome.8b0048330411623PMC6433620Primary2.010.1002/pmic.20140062025913743Primary1.0Hiromi W.L. Kohhiromi_koh@nuhs.edu.sgPersonPrimary contactYunbin Zhangyz2236@nyu.eduPersonPrimary contactChristine Vogelcvogel@nyu.eduPersonPrimary contactHyungwon Choihwchoi@nus.edu.sgPersonPrimary contactInterEvDockAb initio protein docking based on rigid-body sampling followed by consensus scoring using physics-based and statistical potentials, including the InterEvScore function specifically developed to incorporate co-evolutionary information in docking.https://mobyle.rpbs.univ-paris-diderot.fr/cgi-bin/portal.py#forms::InterEvDock2interevdock2biotools:interevdock22.0Web applicationhttp://edamontology.org/topic_2275Molecular modellinghttp://edamontology.org/topic_0128Protein interactionshttp://edamontology.org/topic_0080Sequence analysisFreewareMatureFree of chargeOpen accesshttp://edamontology.org/operation_3899Protein-protein dockinghttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_2877Protein complexhttp://edamontology.org/format_1476PDB

http://edamontology.org/operation_0477Protein modellinghttp://edamontology.org/operation_3899Protein-protein dockinghttp://edamontology.org/data_2976Protein sequencehttp://edamontology.org/format_1929FASTAhttp://edamontology.org/data_2976Protein sequencehttp://edamontology.org/format_1929FASTA

http://edamontology.org/data_2877Protein complexhttp://edamontology.org/format_1476PDB

http://bioserv.rpbs.univ-paris-diderot.fr/services/InterEvDock2/General10.1093/nar/gky37729741647PMC6030979Primary2.010.1093/nar/gkw34027131368PMC4987904Primary1.010.1093/bioinformatics/btt26023652426MethodRaphael Gueroisraphael.guerois@cea.frhttps://orcid.org/0000-0001-5294-2858PersonPrimary contactJessica Andreanijessica.andreani@cea.frPersonPrimary contactHousekeeping and Reference Transcript AtlasRedefining human and mouse housekeeping genes and candidate reference transcripts by mining massive RNA-seq datasets. Web-based tools to search tissue specific housekeeping genes.http://www.housekeeping.unicamp.brHousekeepingbiotools:Housekeeping1.0Web applicationhttp://edamontology.org/topic_0203Gene expressionhttp://edamontology.org/topic_3170RNA-Seqhttp://edamontology.org/topic_3512Gene transcriptshttp://edamontology.org/topic_0632Probes and primershttp://edamontology.org/topic_3518Microarray experimenthttp://edamontology.org/topic_3307Computational biologyhttp://edamontology.org/topic_3361Laboratory techniqueshttp://edamontology.org/topic_3678Experimental design and studiesRFree of chargeOpen accesshttp://edamontology.org/operation_3799Quantificationhttp://edamontology.org/operation_3840Multilocus sequence typinghttp://edamontology.org/operation_2424Comparisonhttp://www.housekeeping.unicamp.brServiceRepositoryDatabase home pagehttps://github.com/Bidossessih/HRT_AtlasRepositoryHrt Atlas Githubhttp://housekeeping.unicamp.br/?aboutGeneral10.1093/nar/gkaa60932663312PMC7778946Primary1.0Bidossessi Wilfried Hounkpebidossessi1@live.frhttp://orcid.org/0000-0002-9992-1939PersonMaintainerFast-GBSFast-GBS is an analysis toolkit for genotyping-by-sequencing data. Genotyping-by-sequencing (GBS) is a rapid, flexible, low-cost, and robust genotyping method that simultaneously discovers variants and calls genotypes within a broad range of samples. These characteristics make GBS an excellent tool for many applications and research questions from conservation biology to functional genomics in both model and non-model species. Continued improvement of GBS relies on a more comprehensive understanding of data analysis, development of fast and efficient bioinformatics pipelines, accurate missing data imputation, and active post-release support.https://bitbucket.org/jerlar73/fast-gbs_v2/src/master/fast-gbsbiotools:fast-gbs2.0http://edamontology.org/topic_0625Genotype and phenotypehttp://edamontology.org/topic_0769Workflowshttp://edamontology.org/operation_3557Imputationhttp://edamontology.org/operation_3196Genotypinghttp://edamontology.org/operation_3227Variant callinghttps://hub.docker.com/repository/docker/jelar5/fast-gbs_v2Container file10.1139/gen-2020-007733006480Primary1.010.1186/s12859-016-1431-928049422PMC5210301Primary1.0PredictSNP2A consensus classifier that combines five of the top performing tools (CADD, DANN, FATHMM, FunSeq2 and GWAVA) for the evaluation of pathogenic effect of SNPs within the human genome. The obtained results are provided together with annotations extracted from dbSNP, GenBank, Clinvar, OMIM, RegulomeDB, HaploReg, UCSC and Ensembl databases.https://loschmidt.chemi.muni.cz/predictsnp2predictsnp2biotools:predictsnp21.0Web applicationhttp://edamontology.org/topic_3063Medical informaticshttp://edamontology.org/topic_2533DNA mutationhttp://edamontology.org/topic_3325Rare diseaseshttp://edamontology.org/topic_0622GenomicsLinuxWindowsMacJavaScriptJavaProprietaryCzech RepublicRare DiseaseELIXIR-CZMatureFree of charge (with restrictions)Open accessToolsCzech Republichttp://edamontology.org/operation_3672Gene functional annotationhttp://edamontology.org/operation_3225Variant classificationhttp://edamontology.org/data_3498Sequence variationshttp://edamontology.org/format_3019GVFhttp://edamontology.org/format_3016VCF

http://edamontology.org/data_3498Sequence variationshttp://edamontology.org/format_3016VCFhttp://edamontology.org/format_3508PDF

VCF file containing scores and PDF file containing scores and database linkshttps://loschmidt.chemi.muni.cz/peg/software/predictsnp2-standalone/Downloads page1.0https://loschmidt.chemi.muni.cz/predictsnp2/docs/userguide.pdfUser manual10.1371/journal.pcbi.100496227224906PMC4880439Primary1.0Jaroslav Bendljaroslav.bendl@gmail.comhttps://orcid.org/0000-0001-9989-2720PersonDeveloperJan Stouracstourac.jan@gmail.comhttps://orcid.org/0000-0003-3139-3700PersonDeveloperSupportMilos Musilxmusil46@stud.fit.vutbr.czhttps://orcid.org/0000-0001-9373-7930PersonDeveloperJan Brezovskybrezovsky@mail.muni.czhttps://orcid.org/0000-0001-9677-5078PersonContributorJiri Damborsky1441@mail.muni.czhttps://orcid.org/0000-0002-7848-8216PersonContributorEric D. WiebenPersonContributorJaroslav Zendulkazendulka@fit.vut.czhttps://orcid.org/0000-0001-8718-7493PersonContributorAntonin Pavelka99207@mail.muni.czPersonDeveloperLoschmidt Laboratorieshttps://loschmidt.chemi.muni.cz/peg/InstituteProviderMasaryk University, Brno, Czech Republichttps://www.muni.cz/InstituteProviderInternational Centre for Clinical Research, Brno, Czech Republichttps://www.fnusa-icrc.org/en/InstituteProviderBrno University of Technology, Brno, Czech Republichttps://www.vutbr.cz/InstituteProviderELIXIR-CZhttps://www.elixir-czech.cz/ConsortiumProviderPredictSNP teampredictsnp@sci.muni.czPersonPrimary contactEuropean Regional Development FundFunding agencyContributorEuropean Social FundFunding agencyContributorGrant Agency of the Czech RepublicFunding agencyContributorMinistry of Education of the Czech RepublicFunding agencyContributorBrno University of TechnologyFunding agencyContributorCaverDockPerforms rapid analysis of transport processes in proteins. It models the transportation of a ligand from outside environment into the protein active or binding site and vice versa. It implements a novel algorithm to produce contiguous ligand trajectory and estimation of a binding energy along the pathway. The current version uses CAVER for pathway identification and heavily modified Autodock Vina as a docking engine.https://loschmidt.chemi.muni.cz/caverdock/caverdockbiotools:caverdock1.01.1Command-line toolhttp://edamontology.org/topic_2814Protein structure analysishttp://edamontology.org/topic_0154Small moleculeshttp://edamontology.org/topic_0078ProteinsLinuxWindowsMacC++PythonProprietaryCAVERELIXIR-CZMatureFree of charge (with restrictions)Tools3D-BioInfoCzech Republichttp://edamontology.org/operation_0482Protein-ligand dockinghttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_1463Small molecule structurehttp://edamontology.org/format_1476PDB

http://edamontology.org/data_1537Protein structure reporthttp://edamontology.org/format_1957rawhttp://edamontology.org/format_1476PDB

trajectory of ligand passing through protein tunnel and its energyhttps://www.fi.muni.cz/~xfilipov/caverdock/caverdock-ubuntu-14.04.tar.gzBinariesv1.0, Ubuntu 14.041.0https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-ubuntu-16.04.tar.gzBinariesv1.0, Ubuntu 16.041.0https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-1.1-ubuntu-16.04.tar.xzBinariesv1.1, Ubuntu 16.041.1https://www.fi.muni.cz/~xfilipov/caverdock/caverdock-1.1-ubuntu-18.04.tar.xzBinariesv1.1, Ubuntu 18.041.1https://www.fi.muni.cz/~xfilipov/caverdock/manual.pdfUser manualversion 1.0https://www.fi.muni.cz/~xfilipov/caverdock/manual-1.1.pdfUser manualversion 1.110.1093/bioinformatics/btz38631077297Primary1.010.1109/tcbb.2019.290749230932844Primary1.0Jiri Filipovicfila@mail.muni.czhttps://orcid.org/0000-0002-5703-9673PersonDeveloperOndrej Vavrao.vavra@mail.muni.czPersonContributorJan Plhak408420@mail.muni.czPersonDeveloperDavid Bednar222755@mail.muni.czhttps://orcid.org/0000-0002-6803-0340PersonContributorSergio Marquessmar96@gmail.comhttps://orcid.org/0000-0002-6281-7505PersonContributorJan Brezovskybrezovsky@mail.muni.czhttps://orcid.org/0000-0001-9677-5078PersonContributorJan Stouracstourac.jan@gmail.comhttps://orcid.org/0000-0003-3139-3700PersonDeveloperSupportLudek MatyskaLudek.Matyska@muni.czhttps://orcid.org/0000-0001-6399-5453PersonContributorJiri Damborsky1441@mail.muni.czhttps://orcid.org/0000-0002-7848-8216PersonContributorLoschmidt Laboratorieshttps://loschmidt.chemi.muni.cz/peg/InstituteProviderMasaryk University, Brno, Czech Republichttps://www.muni.cz/InstituteProviderInternational Centre for Clinical Research, Brno, Czech Republichttps://www.fnusa-icrc.org/en/InstituteProviderELIXIR-CZhttps://www.elixir-czech.cz/ConsortiumProviderCaverDock teamcaver@caver.czPersonPrimary contactEuropean CommissionFunding agencyContributorCzech Science FoundationFunding agencyContributorBrno City MunicipalityFunding agencyContributorPredictSNPA consensus classifier that combines six of the top performing tools for the prediction of the effects of mutation on protein function. The obtained results are provided together with annotations extracted from the Protein Mutant Database and the UniProt database.https://loschmidt.chemi.muni.cz/predictsnp1predictsnpbiotools:predictsnp1.0Command-line toolWeb applicationhttp://edamontology.org/topic_2885DNA polymorphismhttp://edamontology.org/topic_3063Medical informaticshttp://edamontology.org/topic_3325Rare diseaseshttp://edamontology.org/topic_0078Proteinshttp://edamontology.org/topic_3053GeneticsLinuxWindowsMacJavaScriptJavaPythonProprietaryCzech RepublicRare DiseaseELIXIR-CZMatureFree of charge (with restrictions)Open accessToolsCzech Republichttp://edamontology.org/operation_0331Variant effect predictionhttp://edamontology.org/data_2974Protein sequence (raw)http://edamontology.org/format_1929FASTA

http://edamontology.org/data_1277Protein featureshttp://edamontology.org/format_2331HTMLhttp://edamontology.org/format_2330Textual format

http://edamontology.org/data_2291UniProt ID

Prediction of the effect of amino acid substitution on protein functionhttps://loschmidt.chemi.muni.cz/predictsnp1/docs/predictsnp-1.0.tar.gzBinarieshttps://loschmidt.chemi.muni.cz/predictsnp1/docs/USER_GUIDE.pdfUser manualmappusesnssnpanalyzerusespantherusesphd-snpusespolyphenusespolyphen-2usessiftusessnapuses10.1371/journal.pcbi.100344024453961PMC3894168Primary1.0Jaroslav Bendljaroslav.bendl@gmail.comhttps://orcid.org/0000-0001-9989-2720PersonDeveloperJan Stouracstourac.jan@gmail.comhttps://orcid.org/0000-0003-3139-3700PersonDeveloperSupportOndrej SalandaPersonDeveloperJan Brezovskybrezovsky@mail.muni.czhttps://orcid.org/0000-0001-9677-5078PersonContributorJiri Damborsky1441@mail.muni.czhttps://orcid.org/0000-0002-7848-8216PersonContributorEric D. WiebenPersonContributorJaroslav Zendulkazendulka@fit.vut.czhttps://orcid.org/0000-0001-8718-7493PersonContributorAntonin Pavelka99207@mail.muni.czPersonDeveloperLoschmidt Laboratorieshttps://loschmidt.chemi.muni.cz/peg/InstituteProviderMasaryk University, Brno, Czech Republichttps://www.muni.cz/InstituteProviderInternational Centre for Clinical Research, Brno, Czech Republichttps://www.fnusa-icrc.org/en/InstituteProviderBrno University of Technology, Brno, Czech Republichttps://www.vutbr.cz/InstituteProviderMayo Clinic, Rochester, New York, United States of Americahttps://www.mayoclinic.org/InstituteProviderELIXIR-CZhttps://www.elixir-czech.cz/ConsortiumProviderPredictSNP teampredictsnp@sci.muni.czPersonPrimary contactEuropean Regional Development FundFunding agencyContributorEuropean Social FundFunding agencyContributorGrant Agency of the Czech RepublicFunding agencyContributorMinistry of Education of the Czech RepublicFunding agencyContributorBrno University of TechnologyFunding agencyContributorAraQTLAraQTL is the A.thaliana workbench and database for eQTL analysis. It allows easy access to the data of all published Arabidopsis thaliana genetical genomics experiments.https://www.bioinformatics.nl/AraQTLaraqtlbiotools:araqtl1.0Web applicationhttp://edamontology.org/topic_3360Biomarkershttp://edamontology.org/topic_3517GWAS studyhttp://edamontology.org/topic_0625Genotype and phenotypeMaturehttp://edamontology.org/operation_3232Gene expression QTL analysishttp://edamontology.org/operation_0282Genetic mappinghttp://edamontology.org/operation_0224Query and retrieval10.1111/tpj.13457279956641.0Harm Nijveenharm.nijveen@wur.nlhttps://orcid.org/0000-0002-9167-4945PersonDeveloperWilco Ligterinkhttps://orcid.org/0000-0002-0228-169XPersonJoost J. B. Keurentjeshttps://orcid.org/0000-0001-8918-0711PersonOlivier Loudethttps://orcid.org/0000-0003-3717-0137PersonJiao LongPersonMark G. Sterkenhttps://orcid.org/0000-0001-7119-6213PersonPjotr PrinsPersonHenk W. Hilhorsthttps://orcid.org/0000-0002-6743-583XPersonDick de Ridderhttps://orcid.org/0000-0002-4944-4310PersonJan E. KammengaPersonBasten L. Snoekbasten.snoek@wur.nlPersonPrimary contactbamtocovTools to extract coverage informations from BAM (and CRAM) files, based on the covtobed algorithm that supports stranded coverage and physical coverage, input from streams and uses a memory-efficient algorithm.https://telatin.github.io/bamtocov/bamtocovbiotools:bamtocov2.5.02.7.02.8.0Command-line toolLinuxMacCMIThttp://edamontology.org/operation_0260Sequence alignment conversionhttp://edamontology.org/data_1383Nucleic acid sequence alignmenthttp://edamontology.org/format_2572BAMhttp://edamontology.org/format_3462CRAMhttp://edamontology.org/data_3002Annotation trackhttp://edamontology.org/format_3003BED

http://edamontology.org/data_3002Annotation trackhttp://edamontology.org/format_3583bedgraphhttp://edamontology.org/format_3005WIG

https://telatin.github.io/bamtocov/Otherhttps://github.com/telatin/bamtocovRepositoryhttps://anaconda.org/bioconda/bamtocovSoftware catalogue10.1101/2021.11.12.466787MethodPreprint hosted by biorXiv10.1093/bioinformatics/btac12535199151PMC90486501.0Bioinformatics Application note on BamToCovAndrea Telatinhttps://github.com/telatinhttps://orcid.org/0000-0001-7619-281XPersonPrimary contactGiovanni Birolohttps://orcid.org/0000-0003-0160-9312PersonDeveloperCordaxThe amyloid conformation can be adopted by a variety of sequences, but the precise boundaries of amyloid sequence space are still unclear. The currently charted amyloid sequence space is strongly biased towards hydrophobic, beta-sheet prone sequences that form the core of globular proteins and by Q/N/Y rich yeast prions. Here, we took advantage of the increasing amount of high-resolution structural information on amyloid cores currently available in the protein databank to implement a machine learning approach, named Cordax (https://cordax.switchlab.org), that explores amyloid sequence beyond its current boundaries.https://cordax.switchlab.orgcordaxbiotools:cordax1.0http://edamontology.org/topic_0621Model organismsVIBKU Leuven10.1038/s41467-020-17207-332620861PMC7335209Primary1.0Joost Schymkowitzhttps://orcid.org/0000-0003-2020-0168Primary contactPDBinderPDBinder is a bioinformatic method for the prediction of small ligand binding sites in protein structureshttp://cbm.bio.uniroma2.it/pdbinder/pdbinderbiotools:pdbinderhttp://edamontology.org/topic_3534Protein binding siteshttp://edamontology.org/topic_2814Protein structure analysishttp://edamontology.org/topic_0082Structure predictionhttp://edamontology.org/operation_3897Ligand-binding site predictionhttp://edamontology.org/operation_2464Protein-protein binding site predictionhttp://edamontology.org/operation_0420Nucleic acids-binding site predictionhttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1208proteinhttp://edamontology.org/data_1277Protein features10.1186/1471-2105-13-s4-s1722536963PMC3434446Method1.0Plant PTM ViewerThe Plant PTM Viewer is an integrative PTM resource that comprises approximately 370 000 PTM sites for 19 types of protein modifications in plant proteins from five different species.http://www.psb.ugent.be/PlantPTMViewerplant_ptm_viewerbiotools:plant_ptm_viewer1.0Web applicationhttp://edamontology.org/topic_0601Protein modificationshttp://edamontology.org/topic_0780Plant biologyJavaScriptNot licensedVIBUGentBIG N2NMatureFree of chargeOpen accessBelgiumhttp://edamontology.org/operation_3645PTM identificationhttp://edamontology.org/operation_0417PTM site predictionhttps://www.psb.ugent.be/webtools/ptm-viewer/tutorial.phpUser manual10.1111/tpj.1434531004550Primary1.0Patrick WillemsProviderPrimary contactThomas Van ParysDeveloperAlison HorneDeveloperBeyondcellBeyondcell is a computational methodology for identifying tumour cell subpopulations with distinct drug responses in single-cell RNA-seq data and proposing cancer-specific treatments.https://github.com/cnio-bu/beyondcellbeyondcellbiotools:beyondcell2.1Workflowhttp://edamontology.org/topic_3170RNA-Seqhttp://edamontology.org/topic_0208Pharmacogenomicshttp://edamontology.org/topic_2640Oncologyhttp://edamontology.org/topic_2229Cell biologyhttp://edamontology.org/topic_3308TranscriptomicsMacLinuxROtherIMPaCT-DataMatureFree of charge (with restrictions)Open access (with restrictions)http://edamontology.org/operation_3223Differential gene expression profilinghttp://edamontology.org/operation_4009Small molecule designhttp://edamontology.org/operation_0313Expression profile clusteringhttp://edamontology.org/data_3112Gene expression matrixhttp://edamontology.org/format_3752CSVhttp://edamontology.org/format_3475TSVhttp://edamontology.org/data_0928Gene expression profilehttp://edamontology.org/format_1915Format

http://edamontology.org/data_0951Statistical estimate score

http://edamontology.org/data_3768Clustered expression profiles

http://edamontology.org/data_1621Pharmacogenomic test report

Beyondcell can make use of custom gene expression profiles on top of its own catalogue of drug related signatures. Beyondcell allows the user to input a GMT file containing the functional pathways/signatures of interest as well as numeric matrices containing a ranking criteria such as the t-statistic or logFoldChange.https://gitlab.com/bu_cnio/beyondcell/-/issues?sort=updated_desc&state=openedIssue trackerhttps://gitlab.com/bu_cnio/beyondcell/-/archive/master/beyondcell-master.zipSource codeSource code for the current software version1.3.3.https://anaconda.org/bioconda/r-beyondcellSoftware packageConda package for the current software version.1.3.3https://gitlab.com/bu_cnio/beyondcell/-/tree/master/tutorial/analysis_workflowQuick start guidehttps://gitlab.com/bu_cnio/beyondcell/-/tree/master/tutorial/analysis_workflowInstallation instructionshttps://gitlab.com/bu_cnio/beyondcell/-/tree/master/tutorial/analysis_workflowCitation instructionshttps://gitlab.com/bu_cnio/beyondcell/-/blob/master/CHANGELOG.mdRelease notes10.1101/2021.04.08.438954Primary1.0Publication about the methodology and its application in a variety of experimental models, from cancer cell lines to human data.Dr. Fátima Al-Shahrourfalshahrour@cnio.eshttps://orcid.org/0000-0003-2373-769XPersonPrimary contactCNIOInstituteProviderBU_CNIODivisionProviderkmerAnalyzerAn alignment-free method capable of processing and counting k-mers in a reasonable time, while evaluating multiple values of the k parameter concurrently.https://github.com/BiodataAnalysisGroup/kmerAnalyzerkmeranalyzerbiotools:kmeranalyzer1.0Scripthttp://edamontology.org/topic_3293Phylogeneticshttp://edamontology.org/topic_3474Machine learninghttp://edamontology.org/topic_3168Sequencinghttp://edamontology.org/topic_3174Metagenomicshttp://edamontology.org/topic_0196Sequence assemblyMacLinuxWindowsPythonRMITEmergingFree of chargeOpen accessGreecehttp://edamontology.org/operation_3472k-mer countinghttp://edamontology.org/operation_3478Phylogenetic reconstructionhttp://edamontology.org/operation_2422Data retrievalhttp://edamontology.org/operation_3891Essential dynamicshttp://edamontology.org/data_1667E-value10.3389/fgene.2021.61817034122498PMC81942961.0Fotis E. Psomopoulosfpsom@certh.grhttps://orcid.org/0000-0002-0222-4273PersonPrimary contactNikolaos PechlivanisAnastasios TogkousidisIlias KappasKojakA database search algorithm for solving cross-linked peptide mass spectra.https://kojak-ms.systemsbiology.net/kojakbiotools:kojak2.0.0Command-line toolhttp://edamontology.org/topic_0121Proteomicshttp://edamontology.org/topic_3520Proteomics experimenthttp://edamontology.org/topic_0078ProteinsLinuxWindowsC++Apache-2.0MatureFree of chargeOpen accessProteomicshttps://kojak-ms.systemsbiology.net/download.htmlDownloads page1.0 - 2.0.0https://kojak-ms.systemsbiology.net/docs/index.htmlQuick start guideInstallation instructionsUser manualhttps://kojak-ms.systemsbiology.net/param/index.htmlCommand-line options10.1021/pr501321h25812159PMC4428575Primary1.010.1021/acs.jproteome.2c0067036629399PMC10234491Primary2.0.0