pathway-subtypingDisease-agnostic Python framework for discovering molecular subtypes using pathway-level analysis and Gaussian mixture model clustering with built-in validation gateshttps://codeberg.org/pathways/pathway-subtyping-frameworkpathway-subtypingbiotools:pathway-subtyping0.4.00.3.10.5.0LibraryCommand-line toolhttp://edamontology.org/topic_3391Omicshttp://edamontology.org/topic_3307Computational biologyhttp://edamontology.org/topic_3474Machine learninghttp://edamontology.org/topic_4019BiosciencesWindowsMacLinuxPythonMITMatureFree of chargeOpen accesshttp://edamontology.org/operation_3432Clusteringhttp://edamontology.org/operation_2945Data analysishttp://edamontology.org/operation_2495Expression analysishttps://pypi.org/project/pathway-subtyping/Software cataloguePython Library Repositoryhttps://codeberg.org/pathways/pathway-subtyping-framework/src/branch/main/docsOtherDocumentationhttps://codeberg.org/pathways/pathway-subtyping-frameworkOtherSource code repositoryhttps://pypi.org/project/pathway-subtyping/Software packagepip install pathway-subtyping
Or with all extras:
pip install pathway-subtyping[viz,graph]0.3.1https://codeberg.org/pathways/pathway-subtyping-framework/src/branch/main/docsUser manual10.21203/rs.3.rs-8913089/v1PreprintTitle: Pathway-Based Molecular Subtyping Reveals a GABA-Collapsed Autism Subgroup and Cross-Disease Convergence with Schizophrenia in Human Cerebral CortexSLiMEvolutionary simulation framework that combines a powerful engine for population genetic simulations with the capability of modeling arbitrarily complex evolutionary scenarios. Includes a graphical modeling environment.https://messerlab.org/slim/SLiM_softwarebiotools:SLiM_software5.2Command-line toolDesktop applicationhttp://edamontology.org/topic_0610Ecologyhttp://edamontology.org/topic_0602Molecular interactions, pathways and networkshttp://edamontology.org/topic_0199Genetic variationhttp://edamontology.org/topic_3299Evolutionary biologyWindowsLinuxMacC++GPL-3.0MatureFree of chargeOpen accesshttp://edamontology.org/operation_0230Sequence generationhttp://edamontology.org/operation_0550DNA substitution modellinghttp://edamontology.org/operation_3946Ecological modellingRun individual-based eco-evolutionary simulations with explicit geneticshttps://messerlab.org/slim/Software catalogueSLiM home page in the Messer Lab websitehttps://github.com/MesserLab/SLiMRepositoryGitHub repository for SLiMhttps://groups.google.com/g/slim-discussDiscussion forumDiscussion forum for SLiM questionshttps://groups.google.com/g/slim-announceMailing listAnnouncements mailing listhttp://benhaller.com/slim/SLiM.zipSource codeA source archive for the command-line `slim` tool only. Complete source code is on GitHub, but most platforms have an installer anyway; see the manual, chapter 2, for installation instructions.https://github.com/MesserLab/SLiM/releases/latestDownloads pageThe GitHub page for the current release version, to obtain full source code.http://benhaller.com/slim/SLiM_Manual.pdfUser manualThe manual for SLiM itselfhttp://benhaller.com/slim/Eidos_Manual.pdfUser manualThe manual for Eidos, the scripting language used by SLiMhttp://benhaller.com/slim/SLiMEidosRefSheets.zipQuick start guideQuick reference sheets for SLiM and Eidos10.1093/molbev/msy22830517680PMC6389312Primary3.0B.C. Haller, P.W. Messer. (2019). SLiM 3: Forward genetic simulations beyond the Wright–Fisher Model. Molecular Biology and Evolution 36(3), 632–637.10.1093/molbev/msy23730590560PMC6501880Method3.0B.C. Haller, P.W. Messer. (2019). Evolutionary modeling in SLiM 3 for beginners. Molecular Biology and Evolution 36(5), 1101–1109.10.1111/1755-0998.1296830565882PMC6393187Primary3.0B.C. Haller, J. Galloway, J. Kelleher, P.W. Messer, P.L. Ralph. (2019). Tree-sequence recording in SLiM opens new horizons for forward-time simulation of whole genomes. Molecular Ecology Resources 19(2), 552–566.10.1101/2025.08.07.66915540832315PMC12363870Primary5.0BC Haller, PL Ralph, PW Messer. (2025). SLiM 5: Eco-evolutionary simulations across multiple chromosomes and full genomes. bioRxiv, 2025.08. 07.66915510.1086/72360137130229PMC10793872Primary4.0B.C. Haller, P.W. Messer. (2023). SLiM 4: Multispecies eco-evolutionary modeling. The American Naturalist 201(5), E127–E139.Philipp Messermesser@cornell.eduhttps://messerlab.orghttps://orcid.org/0000-0001-8453-9377PersonPrimary contactBenjamin C. Hallerbhaller@benhaller.comhttp://benhaller.comhttps://orcid.org/0000-0003-1874-8327PersonPrimary contactcovsnapCoverage inspector for targeted sequencing QC (hg38)https://github.com/enes-ak/covsnapcovsnapbiotools:covsnap0.3.0Desktop applicationCommand-line toolhttp://edamontology.org/topic_0080Sequence analysishttp://edamontology.org/topic_3572Data quality managementMacWindowsLinuxPythonOtherEmergingFree of chargeOpen accesshttp://edamontology.org/operation_3180Sequence assembly validationhttp://edamontology.org/data_1383Nucleic acid sequence alignmenthttp://edamontology.org/format_2572BAMcovsnap sample.bam BRCA1,TP53,ETFDH --exonshttps://pypi.org/project/covsnap/RepositoryInstall with: pip install covsnaphttps://github.com/enes-ak/covsnapRepositorygithub repositoryhttps://anaconda.org/channels/bioconda/packages/covsnap/overviewRepositoryInstall with: conda install -c bioconda covsnaphttps://pypi.org/project/covsnap/Downloads pagepip install covsnap0.3.0https://anaconda.org/channels/bioconda/packages/covsnap/overviewDownloads pagehttps://anaconda.org/channels/bioconda/packages/covsnap/overviewhttps://github.com/enes-ak/covsnap/blob/master/README.mdGeneralEnes Akakenes96@gmail.comhttps://orcid.org/0000-0001-5931-730XDeveloperSAMBO OptimizationSequential and model-based optimization for Python with state-of-the-art performance.https://sambo-optimization.github.io/sambo_sequential_model-based_optimizationbiotools:sambo_sequential_model-based_optimizationv1.25.2Libraryhttp://edamontology.org/topic_3569Applied mathematicshttp://edamontology.org/topic_0092Data visualisationhttp://edamontology.org/topic_3474Machine learningAGPL-3.0MatureFree of chargeOpen accesshttp://edamontology.org/operation_2425Optimisation and refinementhttps://github.com/sambo-optimization/samboRepositoryhttps://github.com/sambo-optimization/sambo/issuesIssue trackerhttps://sambo-optimization.github.io/doc/sambo/API documentation10.5281/zenodo.14461363pathotyprA fast, offline, pathogen-agnostic toolkit for lineage classification and marker-driven genotyping from whole-genome sequencing data. Bring your own SNP marker panel for any microbial pathogen — pathotypr handles the rest. Ships with curated panels for Mycobacterium tuberculosis complex (MTBC): 3,707 lineage-defining SNPs and over 102,000 resistance-associated mutations. Works with assembled genomes (FASTA) and raw reads (FASTQ). Available as command-line interface and cross-platform desktop GUI (Tauri).https://github.com/PathoGenOmics-Lab/pathotyprpathotyprbiotools:pathotypr1.0.0Command-line toolDesktop applicationhttp://edamontology.org/topic_0622Genomicshttp://edamontology.org/topic_3301Microbiologyhttp://edamontology.org/topic_0625Genotype and phenotypehttp://edamontology.org/topic_3168Sequencinghttp://edamontology.org/topic_3305Public health and epidemiologyhttp://edamontology.org/topic_3474Machine learningRustAGPL-3.0MatureFree of chargeOpen accesshttp://edamontology.org/operation_3196Genotypinghttp://edamontology.org/data_2044Sequencehttp://edamontology.org/format_1929FASTAtrain — Build a Random Forest classifier from labeled genomes.http://edamontology.org/operation_3225Variant classificationhttp://edamontology.org/data_2044Sequencehttp://edamontology.org/format_1929FASTApredict — Assign lineages to genomes using a pre-trained Random Forest model.http://edamontology.org/operation_3196Genotypinghttp://edamontology.org/operation_3225Variant classificationhttp://edamontology.org/data_2044Sequencehttp://edamontology.org/format_1929FASTAclassify — Call known SNP markers in assembled genomes against a user-defined marker panel.http://edamontology.org/operation_3196Genotypinghttp://edamontology.org/data_2044Sequencehttp://edamontology.org/format_1930FASTQsplit-fastq — Alignment-free genotyping directly from raw reads using k-mer matching.http://edamontology.org/operation_0346Sequence similarity searchhttp://edamontology.org/data_2044Sequencehttp://edamontology.org/format_1930FASTQmatch — Find the closest reference genome from a set of references for raw reads.https://github.com/PathoGenOmics-Lab/pathotypr/releasesBinarieshttps://github.com/PathoGenOmics-Lab/pathotyprSource codehttps://github.com/PathoGenOmics-Lab/pathotypr/tree/main/docsUser manual10.64898/2026.03.24.714002PrimaryPaula Ruiz-Rodriguezhttps://orcid.org/0000-0003-0727-5974PersonDeveloperMaintainerMireia Coscollahttps://orcid.org/0000-0003-0752-0538PersonPrimary contactI2SysBio (CSIC - Universitat de València)InstituteProviderPathoGenOmics LabDivisionProviderEUCAIM ETL toolsetModular toolchain for an extensible and customizable ETL pipeline that extracts, transforms, and loads clinical data and medical imaging metadata, applying dataset-specific mappings to generate outputs compatible with the EUCAIM Common Data Model (CDM). Its design aims to minimize manual data preparation efforts and facilitate customization and integration with other components, such as data quality assurance tools.
Containerized, currently supports input datasets in CSV, JSON, XLSX.https://github.com/EUCAIM/etl-toolset/eetl_toolsetbiotools:eetl_toolset0.1.10.1.20.2.1LibraryWorkflowhttp://edamontology.org/topic_3345Data identity and mappinghttp://edamontology.org/topic_0769WorkflowsLinuxWindowsJavaPythonApache-2.0EUCAIMEmergingFree of chargeOpen access (with restrictions)ToolsSpainhttp://edamontology.org/operation_0335Data formattinghttp://edamontology.org/operation_3431Data depositionhttp://edamontology.org/operation_0336Format validationhttps://github.com/EUCAIM/etl-toolset/Repositoryhttps://docs.google.com/document/d/1QNiqAvVVVsg_3-YuUp1YGNWwakL8yap-GeneralTool documentation from EUCAIM WP5 Task Force 2 efforttabular_data_curatorusesAutoencoder_RF_TabPFN for Cross-Cancer MetabolomicsAccurate and rapid disease diagnosis, particularly in prostate cancer (PC) and breast cancer (BC), is critical for early intervention and improved patient outcomes. Metabolomic signatures represent a robust molecular framework for elucidating cancer-associated biochemical reprogramming. The use of Artificial Intelligence (AI) in biology in recent years has become widespread and promising. This study introduces a novel predictive method that integrates an Autoencoder, random forest based feature selection and Tabular Prior-data Fitted Network (TabPFN) to achieve high diagnostic accuracy from metabolomics data of prostate and breast cancer patients.https://github.com/SvenHauns/metabolomic_classifier.gitautoencoder_rf_tabpfn_for_cross-cancer_metabolomicsbiotools:autoencoder_rf_tabpfn_for_cross-cancer_metabolomicsCommand-line toolhttp://edamontology.org/topic_2815Human biologyhttp://edamontology.org/topic_0091Bioinformaticshttp://edamontology.org/topic_3474Machine learningPythonMITEmergingFree of chargeOpen accesshttp://edamontology.org/operation_2990Classificationpython main.py --dataset {dataset_to_be_used} --setting {ae or rf} --size {size}
python main.py --test_dataset {./data/toy_predict.csv} --dataset {./data/toy_train.csv} --predict True --setting {ae or rf} --size {size}
see Readme for detailed instructionshttps://github.com/SvenHauns/metabolomic_classifier.gitRepositoryhttps://github.com/SvenHauns/metabolomic_classifier.gitSource codehttps://github.com/SvenHauns/metabolomic_classifier.gitUser manualSven Haunshaunss@informatik.uni-freiburg.dePersonContributorGromacsVersatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. It is primarily designed for biochemical molecules like proteins, lipids and nucleic acids that have a lot of complicated bonded interactions, but since it is extremely fast at calculating the nonbonded interactions (that usually dominate simulations) many groups are also using it for research on non-biological systems, e.g. polymers.http://www.gromacs.org/gromacsbiotools:gromacsCommand-line toolLibrarySuitehttp://edamontology.org/topic_0176Molecular dynamicsLinuxLGPL-2.1BioExcelMatureFree of chargehttp://edamontology.org/operation_2476Molecular dynamicshttp://edamontology.org/data_0883Structurehttp://edamontology.org/format_1476PDBhttp://www.gromacs.org/DownloadsSoftware packagehttp://www.gromacs.org/DocumentationGeneral10.1016/j.softx.2015.06.001Benchmarking study10.1002/jcc.2029116211538Benchmarking study10.1063/5.001851633032406Benchmarking study10.1007/978-3-319-15976-8_1Benchmarking study10.1093/bioinformatics/btt05523407358PMC360559910.1021/ct700301q26620784Benchmarking study10.1007/s008940100045Benchmarking study10.1016/0010-4655(95)00042-EBenchmarking study10.1002/jcc.2403026238484PMC5042102Benchmarking study10.1002/jcc.2601131260119Benchmarking studyGROMACS supporthttp://www.gromacs.org/support/mailing_listsPersonPrimary contactquacQuaC is a snakemake-based pipeline that runs several QC tools for WGS/WES samples and then summarizes their results using pre-defined, configurable QC thresholds.https://github.com/uab-cgds-worthey/quacquacbiotools:quac2.0Command-line toolhttp://edamontology.org/topic_0080Sequence analysisPythonGPL-3.0SequencingMatureFree of chargeOpen accesshttp://edamontology.org/operation_3218Sequencing quality controlhttps://github.com/uab-cgds-worthey/quacRepositoryhttps://github.com/uab-cgds-worthey/quac/releases/tag/2.0Source code2.0https://quac.readthedocs.io/General10.21105/joss.05313Manavalan Gajapathyhttps://github.com/ManavalanGhttps://orcid.org/0000-0002-8606-0113PersonPrimary contactRosalutionRosalution assists researchers study genetic variation 🧬 in patients 🧑🏾🤝🧑🏼 by helping select candidate animal models 🐀🐁🐠🪱 to replicate the variation to further research to derive, diagnose, and provide therapies for ultra-rare diseases. Developed by the UAB Center for Computational Genomics and Data Science (CGDS).https://github.com/uab-cgds-worthey/rosalutionrosalutionbiotools:rosalution0.8.8-erWeb applicationhttp://edamontology.org/topic_0199Genetic variationJavaScriptPythonGPL-3.0Rare DiseaseMatureFree of chargehttps://github.com/uab-cgds-worthey/rosalutionRepositoryhttps://github.com/uab-cgds-worthey/rosalution/issuesIssue trackerhttps://github.com/uab-cgds-worthey/rosalution/releases/tag/0.8.8-erSource code0.8.8-er10.21105/joss.05443Angelina Uno-Antonisonhttps://github.com/SeriousHorncatLab Integrated Data (LabID)Lab Integrated Data (LabID) is an open-source web-based platform for research data management in life science institutes, featuring sample and dataset management, an inventory management system and an electronic lab notebook. LabID allows recording extensive experimental information about the provenance of data (samples, reagents, instrument, protocols, assay parameters) and is designed to help individual scientists, research groups and core facilities better manage, annotate and share their research according to FAIR principles.https://grp-gbcs.embl-community.io/labid-user-docs/labidbiotools:labidWeb applicationCommand-line toolhttp://edamontology.org/topic_3070Biologyhttp://edamontology.org/topic_0219Data curation and archivalhttp://edamontology.org/topic_4012FAIR datahttp://edamontology.org/topic_0769Workflowshttp://edamontology.org/topic_3071Data managementMITMatureFree of chargeOpen accesshttps://gitlab.com/lab-integrated-dataRepositoryOpen source repositories for the LabID subprojects (UI, Server, Command Line Interface, Library)https://join.slack.com/t/labintegrateddata/shared_invite/zt-2eb4ivxyc-1C4RZP_For0uiWcHeiTw0QDiscussion forumChannel for questions from externalshttps://www.embl.org/groups/modis/OtherWebsite of the MODIS team behind LabIDhttps://grp-gbcs.embl-community.io/labid-user-docs/GeneralMain documentation including installation instructions and traininghttps://labid-demo.embl.de/Training materialTest server for e.g LabID and trainingsCharles Girardothttps://orcid.org/0000-0003-4301-3920PersonMaintainerPrimary contactDeveloperHead of MODIS team at EMBL HeidelbergJelle Scholtalbershttps://orcid.org/0000-0002-6090-2482PersonDeveloperSupportFormer MODIS team member, now working as a freelance (LabRise solutions)Matthias MonfortPersonMaintainerDeveloperSupportNayeem Rezahttps://orcid.org/0000-0003-2068-5812PersonDeveloperMaintainerSupportLaurent Thomaslaurent.thomas@embl.dehttps://orcid.org/0000-0001-7686-3249PersonDeveloperEMBL Heidelberg03mstc592Institutebio.toolsThe community registry of computational tools and data resources for biosciences.https://bio.toolsbio.toolsbiotools:bio.toolsRRID:SCR_014695rridWeb APIDatabase portalWeb applicationhttp://edamontology.org/topic_0089Ontology and terminologyhttp://edamontology.org/topic_0091Bioinformaticshttp://edamontology.org/topic_0219Data curation and archivalhttp://edamontology.org/topic_3307Computational biologyJavaScriptPythonGPL-3.0EmergingFree of chargeOpen accessToolsDenmarkhttp://edamontology.org/operation_2422Data retrievalhttp://edamontology.org/data_3671Texthttp://edamontology.org/format_1964plain text format (unformatted)https://biotools.readthedocs.io/en/latest/support.html?highlight=helpHelpdeskhttps://github.com/bio-tools/biotoolsregistry/issuesIssue trackerhttps://biotools.readthedocs.io/en/latest/contributors_guide.html#mailing-listMailing listhttps://github.com/bio-tools/biotoolsregistry/Repositoryhttps://github.com/bio-tools/biotoolsRegistrySource codehttps://biotools.readthedocs.io/en/latest/api_usage_guide.htmlAPI documentationAPI usage guidehttps://biotools.readthedocs.io/en/latest/api_reference.htmlAPI documentationAPI Referencehttps://biotools.readthedocs.io/en/latest/publications.html#citationCitation instructionshttps://biotools.readthedocs.io/en/latest/contributors_guide.htmlContributions policyhttps://biotools.readthedocs.io/en/latest/Generalhttps://biotools.readthedocs.io/en/latest/governance.htmlGovernancehttps://biotools.readthedocs.io/en/latest/curators_guide.htmlUser manualCurators Guide10.1093/nar/gkv1116Primary10.12688/f1000research.12974.1Other10.1093/gigascience/gix022Other10.1007/s10009-015-0392-zOtherContributorshttps://biotools.readthedocs.io/en/latest/contributors.htmlPersonThe MINERVA PlatformThe MINERVA (Molecular Interaction NEtwoRk VisuAlization) platform is a standalone webserver for visualization, exploration and management of molecular networks encoded in SBGN-compliant format, including files produced using CellDesigner or SBGN editors. Visualization of uploaded networks generated by the platform is accessible via a web browser to all viewers with the weblink to the resource.
The MINERVA Platform is a webservice using the Java Server Faces 2 technology. The server side, including data parsing, integration, annotation and verification, is implemented in Java. The platform uses the Postgres SQL database for data storage and the Hibernate framework as a middle layer between web server and database. The user web-interface is generated using React.js. The displayed content is visualized by OpenLayers API, dedicated JavaScript and CSS.https://minerva.uni.luMINERVA_Platformbiotools:MINERVA_Platform13.1.313.2.014.0.1315.0.316.4.017.1.318.1.119.1.019.1.320.0.3http://edamontology.org/topic_0602Molecular interactions, pathways and networkshttp://edamontology.org/topic_3391Omicshttp://edamontology.org/topic_3342Translational medicinehttp://edamontology.org/topic_2259Systems biologyAGPL-3.0LCSBELIXIR-LUMatureFree of chargeOpen accessToolsLuxembourghttp://edamontology.org/operation_3926Pathway visualisationVisualise systems biology diagrams online, on a standalone web serverhttp://edamontology.org/operation_0571Expression data visualisationVisualise omics data from multiple datasets on top of the diagramshttp://edamontology.org/operation_3434ConversionConvert between main systems biology layout formats: CellDeslgners SBML, SBML layout+render, SBGN-ML, GPMLhttp://edamontology.org/operation_2426Modelling and simulationUse MINERVA API to access systems biology formats for modellinghttps://gitlab.lcsb.uni.lu/minerva/core/RepositoryGiLab repository for core functionalities (data and format handling, service stability, API access)https://gitlab.lcsb.uni.lu/minerva/core/-/issuesIssue trackerIssue tracker for core functionalities (data and format handling, service stability, API access)https://gitlab.lcsb.uni.lu/minerva/frontendRepositoryGiLab repository for frontend functionalitieshttps://gitlab.lcsb.uni.lu/minerva/frontend/-/issuesIssue trackerIssue tracker for frontend functionalitieshttps://minerva.pages.uni.lu/doc/install/OtherInstallation instructions, including debian package, virtual machine images and docker containers.13.1.3 - 20.0.3https://minerva.uni.luQuick start guideRelease notesUser manualAPI documentationCitation instructionsTerms of usepathvisiousessbgnuseslibsbmluses10.1038/npjsba.2016.2028725475PMC5516855Primary10.010.1093/bioinformatics/btz28631074494PMC6821317Primary12.2.310.1093/bib/bbz06731273380PMC7373180Primary13.1.110.1089/big.2015.005727441714PMC4932659Usage10.010.1016/j.envpol.2019.04.0053099127913.1.1Marek Ostaszewskihttps://orcid.org/0000-0003-1473-370XPersonPrimary contactPiotr Gawronhttps://orcid.org/0000-0002-9328-8052PersonDeveloperReinhard Schneiderhttps://orcid.org/0000-0002-8278-1618PersonProviderVenkata Satagopamhttps://orcid.org/0000-0002-6532-5880PersonSupportRudi Ballinghttps://orcid.org/0000-0003-2902-5650PersonProviderDavid Hokszahttps://orcid.org/0000-0003-4679-0557PersonContributorEwa Smulahttps://orcid.org/0000-0001-7118-3164PersonMaintainerHyPPIHyPPI classifies a protein-protein complex based on its interaction type into permanent, transient, or crystal artifact. Permanent protein-protein complexes are only stable in their complexed state. Their subunits would denature upon dissociation of the protein-protein complex. Transient protein-protein complexes are stable in the complexed as well as in the monomeric form, depending on the necessary function of the complex. Crystal artifacts have no biological function and are artificially formed during the crystallization process. The discrimination is performed using two characteristics of the protein-protein complex, the hydrophobicity of the interface (ΔGhydrophobic) and the quotient of interface area ratios (IF-quotient). The IF-quotient considers whether the protein-protein interface is symmetric.https://proteins.plus/help/ppippibiotools:ppiWeb APIWeb servicehttp://edamontology.org/topic_0128Protein interactionshttp://edamontology.org/topic_0602Molecular interactions, pathways and networksWindowsLinuxMacOtherde.NBIde.NBI-biodataLegacyFree of chargeToolsGermanyhttp://edamontology.org/operation_2406Protein structure analysishttp://edamontology.org/operation_2949Protein-protein interaction analysishttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDBProbability score for interface classificationhttps://proteins.plusServiceA web service to run HyPPI calculations for protein structures stored in the Protein Data Bank or uploaded structures.https://proteins.plus/help/ppi_restServiceA web API to run HyPPI calculations for protein structures stored in the Protein Data Bank or uploaded structures.https://proteins.plus/help/indexGeneral10.1007/s10822-012-9626-223269578Method10.1093/nar/gkx333PrimaryUsageProteinsPlus Supportproteinsplus.zbh@lists.uni-hamburg.dePrimary contactPrimary Contact for Web Service IssuesUniversity of Hamburg, ZBH - Center for Bioinformatics00g30e956InstituteProviderMETALizerMETALizer predicts the coordination geometry of metal ions in metalloproteins. Users can compare potential coordination geometries to those found in the examined structure. The predicted coordination geometries and the observed metal interaction distances can be interactively compared to statistics calculated based on the PDB.https://www.zbh.uni-hamburg.de/en/forschung/amd/software/metalizer.htmlmetalizerbiotools:metalizerWeb APIWeb servicehttp://edamontology.org/topic_0128Protein interactionshttp://edamontology.org/topic_3534Protein binding siteshttp://edamontology.org/topic_0160Sequence sites, features and motifshttp://edamontology.org/topic_2814Protein structure analysishttp://edamontology.org/topic_3336Drug discoveryhttp://edamontology.org/topic_3473Data mininghttp://edamontology.org/topic_0091Bioinformaticshttp://edamontology.org/topic_0092Data visualisationhttp://edamontology.org/topic_0602Molecular interactions, pathways and networkshttp://edamontology.org/topic_0123Protein propertiesWindowsMacLinuxOtherde.NBIde.NBI-biodataMatureFree of chargeToolsGermanyhttp://edamontology.org/operation_2480Structure analysishttp://edamontology.org/operation_3898Metal-binding site predictionhttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_1461Protein-ligand complexhttp://edamontology.org/format_3814SDFhttp://edamontology.org/format_1476PDBhttps://proteins.plusServiceA web service to run METALizer calculations for protein structures stored in the Protein Data Bank.https://proteins.plus/help/metalizer_restServiceA web API to run METALizer calculations for protein structures stored in the Protein Data Bank.https://proteins.plus/help/indexGeneral10.1093/nar/gkaa235PrimaryProteinsPlus Supportproteinsplus.zbh@lists.uni-hamburg.dePrimary contactPrimary Contact for Web Service IssuesUniversity of Hamburg, ZBH - Center for Bioinformatics00g30e956InstituteProviderDoGSiteScorerDoGSiteScorer is a grid-based automated pocket detection and analysis tool. It applies a Difference of Gaussian filter to detect potential binding pockets and splits them into sub-pockets. The method solely uses the 3D structure of the protein. Global properties, describing the size, shape, and chemical features of the predicted (sub-)pockets, are calculated. Per default, a simple druggability score based on a linear combination of the three descriptors describing volume, hydrophobicity, and enclosure is provided for each (sub-)pocket. Furthermore, a subset of meaningful descriptors is incorporated in a support vector machine (libsvm) to predict the (sub-)pocket druggability score (values are between zero and one). The higher the score, the more druggable the pocket is estimated to be.https://www.zbh.uni-hamburg.de/en/forschung/amd/software/dogsitescorer.htmldogsitescorerbiotools:dogsitescorerWeb APIWeb servicehttp://edamontology.org/topic_3534Protein binding siteshttp://edamontology.org/topic_3474Machine learninghttp://edamontology.org/topic_2814Protein structure analysishttp://edamontology.org/topic_3336Drug discoveryhttp://edamontology.org/topic_2275Molecular modellinghttp://edamontology.org/topic_0091Bioinformaticshttp://edamontology.org/topic_0123Protein propertiesWindowsMacLinuxOtherde.NBIde.NBI-biodataMatureFree of chargeToolsGermanyhttp://edamontology.org/operation_2406Protein structure analysishttp://edamontology.org/operation_1777Protein function predictionhttp://edamontology.org/operation_3897Ligand-binding site predictionhttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_1461Protein-ligand complexhttp://edamontology.org/format_3814SDFhttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_3021UniProt accessionComputational detection of protein binding pockets Protein binding pockets Property statistics of all protein binding pocketshttps://proteins.plusServiceA web service to run DoGSiteScorer calculations for protein structures stored in the Protein Data Bank and AlphaFold Protein Structure Database.https://proteins.plus/help/dogsite_restServiceA web API to run DoGSiteScorer calculations for protein structures stored in the Protein Data Bank and AlphaFold Protein Structure Database.https://proteins.plus/help/indexGeneral10.1021/ci100241y20945875MethodPrimary10.1093/bioinformatics/bts31022628523MethodProteinsPlus Supportproteinsplus.zbh@lists.uni-hamburg.dePrimary contactPrimary Contact for Web Service IssuesUniversity of Hamburg, ZBH - Center for Bioinformatics00g30e956InstituteProviderGeoMineGeoMine enables the automated mining of protein-ligand binding sites. Based on individually designed queries, users can search for spatial interaction patterns in huge collections of protein-ligand complexes and binding pockets. The regularly updated GeoMine database relies on the free database systems SQLite and PostgreSQL. It supports radius-based pockets (based on ligands and predicted pockets (based on DoGSite3) for query generation. The query management is based on XML (for the REST service) or JSON in the GUI mode. Its output consists of the query-based superpositions of the matched binding sites and statistics on matching points, distances, and angles.https://www.zbh.uni-hamburg.de/forschung/amd/software/geomine.htmlgeominebiotools:geomineWeb APIWeb servicehttp://edamontology.org/topic_0128Protein interactionshttp://edamontology.org/topic_3473Data mininghttp://edamontology.org/topic_0091Bioinformaticshttp://edamontology.org/topic_3510Protein sites, features and motifshttp://edamontology.org/topic_0081Structure analysishttp://edamontology.org/topic_3336Drug discoveryWindowsMacLinuxOtherde.NBIde.NBI-biodataMatureFree of chargeToolsGermanyhttp://edamontology.org/operation_0306Text mininghttp://edamontology.org/operation_2421Database searchhttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_1461Protein-ligand complexhttp://edamontology.org/format_3814SDFhttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_3021UniProt accessionhttps://proteins.plusServiceA web service to run GeoMine calculations for protein structures stored in the Protein Data Bank and AlphaFold Protein Structure Database.https://proteins.plus/help/geomine_restServiceA web API to run GeoMine calculations for protein structures stored in the Protein Data Bank and AlphaFold Protein Structure Database.https://proteins.plus/help/indexGeneraldogsite3usesprotossuses10.1093/bioinformatics/btaa69332735322Usage10.1021/acs.jcim.6b00561Method10.1021/acs.jmedchem.1c01046Primary10.1007/s10822-024-00563-3UsageProteinsPlus Supportproteinsplus.zbh@lists.uni-hamburg.dePrimary contactPrimary Contact for Web Service IssuesUniversity of Hamburg, ZBH - Center for Bioinformatics00g30e956InstituteProviderProtossProtoss is a fully automated hydrogen atom placement tool for protein-ligand complexes. It adds missing hydrogen atoms to protein structures and detects reasonable protonation states, tautomeric states, and hydrogen coordinates of both protein and ligand molecules by optimizing the hydrogen bond network.https://www.zbh.uni-hamburg.de/en/forschung/amd/software/protoss.htmlprotossbiotools:protossWeb APIWeb servicehttp://edamontology.org/topic_0128Protein interactionshttp://edamontology.org/topic_0602Molecular interactions, pathways and networkshttp://edamontology.org/topic_1317Structural biologyhttp://edamontology.org/topic_0091Bioinformaticshttp://edamontology.org/topic_2275Molecular modellinghttp://edamontology.org/topic_3336Drug discoveryhttp://edamontology.org/topic_3534Protein binding siteshttp://edamontology.org/topic_0082Structure predictionMacLinuxWindowsOtherde.NBIde.NBI-biodataMatureFree of chargeToolsGermanyhttp://edamontology.org/operation_0394Hydrogen bond calculationhttp://edamontology.org/operation_2949Protein interaction analysishttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_1461Protein-ligand complexhttp://edamontology.org/format_3814SDFhttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_3021UniProt accessionhttps://proteins.plusServiceA web service to run Protoss calculations.https://proteins.plus/help/protoss_restServiceA web API to run Protoss calculations.https://proteins.plus/help/indexGeneralgeomineusedByjamdausedBy10.1186/1758-2946-6-1224694216PMC4019353Primary10.1186/1758-2946-1-1320298519PMC3225823OtherProteinsPlus Supportproteinsplus.zbh@lists.uni-hamburg.dePrimary contactPrimary Contact for Web Service IssuesUniversity of Hamburg, ZBH - Center for Bioinformatics00g30e956InstituteProviderPoseEditPoseEdit automatically generates 2D diagrams of protein-ligand complexes, focusing on the interactions between protein and ligand. Interactions between molecules are estimated by an underlying interaction model that relies on atom types and simple geometric criteria. The structure mining tool GeoMine also uses this model to describe binding sites. In addition, users can manipulate the diagrams by translating, rotating, mirroring parts of the structure, adding additional interactions, or removing them. Furthermore, users can add individual labels or adjust available labels. Users can download the final 2D diagrams for a binding site of interest in JSON or SVG format.https://www.zbh.uni-hamburg.de/en/forschung/amd/software/poseedit.htmlposeeditbiotools:poseeditWeb APIWeb servicehttp://edamontology.org/topic_0128Protein interactionshttp://edamontology.org/topic_0092Data visualisationhttp://edamontology.org/topic_0602Molecular interactions, pathways and networkshttp://edamontology.org/topic_0091Bioinformaticshttp://edamontology.org/topic_3336Drug discoveryhttp://edamontology.org/topic_2814Protein structure analysishttp://edamontology.org/topic_3534Protein binding sitesMacLinuxWindowsOtherde.NBIde.NBI-biodataMatureFree of chargeToolsGermanyhttp://edamontology.org/operation_3925Network visualisationhttp://edamontology.org/operation_0570Structure visualisationhttp://edamontology.org/operation_0248Residue interaction calculationhttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_1461Protein-ligand complexhttp://edamontology.org/format_3814SDFhttp://edamontology.org/format_1476PDBhttps://proteins.plusServiceA web service to run PoseEdit calculations for protein-ligand complexes.https://proteins.plus/help/poseview2_restServiceA web API to run PoseEdit calculations for protein-ligand complexes.https://proteins.plus/help/indexGeneralgeomineusedByprotossuses10.1007/s10822-023-00522-437515714PMC10440272PrimaryProteinsPlus Supportproteinsplus.zbh@lists.uni-hamburg.dePrimary contactPrimary Contact for Web Service IssuesUniversity of Hamburg, ZBH - Center for Bioinformatics00g30e956InstituteProviderPoseViewPoseView automatically generates 2D diagrams of protein-ligand complexes, focusing on the interactions between protein and ligand. Interactions between molecules are estimated by an underlying interaction mode that relies on atom types and simple geometric criteria. It adheres to the conventions of chemical structure diagram generation. The quality of the resulting diagrams is comparable to manually drawn examples from books and scientific publications.https://www.zbh.uni-hamburg.de/en/forschung/amd/software/poseview.htmlposeviewbiotools:poseviewWeb APIWeb servicehttp://edamontology.org/topic_0128Protein interactionshttp://edamontology.org/topic_0092Data visualisationhttp://edamontology.org/topic_0602Molecular interactions, pathways and networkshttp://edamontology.org/topic_0091Bioinformaticshttp://edamontology.org/topic_3336Drug discoveryhttp://edamontology.org/topic_2814Protein structure analysishttp://edamontology.org/topic_3534Protein binding sitesMacLinuxWindowsOtherde.NBIde.NBI-biodataMatureFree of chargeToolsGermanyhttp://edamontology.org/operation_3925Network visualisationhttp://edamontology.org/operation_0570Structure visualisationhttp://edamontology.org/operation_0248Residue interaction calculationhttp://edamontology.org/data_1460Protein structurehttp://edamontology.org/format_1476PDBhttp://edamontology.org/data_1461Protein-ligand complexhttp://edamontology.org/format_3814SDFhttp://edamontology.org/format_1476PDBhttps://proteins.plusServiceA web service to run PoseView calculations for protein-ligand complexes.https://proteins.plus/help/poseview_restServiceA web API to run PoseView calculations for protein-ligand complexes.https://proteins.plus/help/indexGeneral10.1021/ml100164p24900245PMC4007829Primary10.1093/bioinformatics/btl15016632493Benchmarking study10.1002/cmdc.20070001017436259Benchmarking study10.1021/ci049958u15154775MethodProteinsPlus Supportproteinsplus.zbh@lists.uni-hamburg.dePrimary contactPrimary Contact for Web Service IssuesUniversity of Hamburg, ZBH - Center for Bioinformatics00g30e956ProviderGRNsightWeb application and service for visualizing small- to medium-scale models of gene regulatory networks. It automatically lays out either an unweighted or weighted network graph based on an Excel input spreadsheet containing an adjacency matrix where regulators are named in the columns and target genes in the rows. It is best-suited for visualizing networks of fewer than 35 nodes and 70 edges and has general applicability.http://dondi.github.io/GRNsight/grnsightbiotools:grnsight7.6.0Web applicationhttp://edamontology.org/topic_0602Molecular interactions, pathways and networkshttp://edamontology.org/topic_0204Gene regulationWindowsMacLinuxJavaScriptBSD-3-ClauseMatureFree of chargehttp://edamontology.org/operation_3083Pathway or network visualisationhttp://edamontology.org/operation_1781Gene regulatory network analysisGRNsight automatically lays out a network graph based on an Excel input spreadsheet containing an adjacency matrix where regulators are named in the columns and target genes in the rows. When a user uploads a spreadsheet with an unweighted adjacency matrix, GRNsight automatically lays out the graph using black lines and pointed arrowheads. When a user uploads a spreadsheet with a weighted adjacency matrix, GRNsight uses pointed and blunt arrowheads, and colors the edges and adjusts their thicknesses based on the sign (positive for activation or negative for repression) and magnitude of the weight parameter. Nodes are rectangular and support gene labels of up to 12 characters. The edges are arcs, which become straight lines when the nodes are close together. Self-regulatory edges are indicated by a loop on the lower-right side of a node. Visualizations can be modified by sliders that adjust D3.js's force graph layout parameters and through manual node dragging.https://github.com/dondi/GRNsightRepositoryhttps://github.com/dondi/GRNsight/archive/refs/heads/main.zipSource codehttp://dondi.github.io/GRNsight/documentation.htmlGeneral10.7717/peerj-cs.85Other10.5281/zenodo.7411630OtherAlex MillerPersonDeveloperJia Celyne GarciaPersonDeveloperCindy TongPersonDeveloperAmelie DinhPersonDeveloperMilka ZekariasPersonDeveloperNgoc Kim Ngan TranPersonDeveloperCecilia ZaragozaPersonDeveloperA’Kaia PhelpsPersonDeveloperOna O. IgbinedionPersonDeveloperAhmad R. MersaghianPersonDeveloperIan M. GreenPersonDeveloperLauren L. AmparoPersonDeveloperAlexia M. FillerPersonDeveloperKevin B. PattersonPersonDeveloperJohn L. LopezPersonDeveloperJustin Kyle T. TorresPersonDeveloperEileen ChoePersonDeveloperJen ShinPersonDeveloperMihir SamdarshiPersonDeveloperAnindita VarshneyaPersonDeveloperNicole A. AnguianoPersonDeveloperBritain J. SouthwickPersonDeveloperBen G. FitzpatrickPersonDeveloperLoyola Marymount UniversityInstituteProviderNSF award 0921038; LMU Rains Research Assistant Program; LMU Summer Undergraduate Research ProgramFunding agencyContributorlmu.eduInstituteProviderKam D. Dahlquistkdahlquist@lmu.eduPersonPrimary contactJohn David N. Dionisiodondi@lmu.eduhttps://orcid.org/0000-0001-8655-4693PersonPrimary contactPangyPlotPangyPlot is a tool for visualizing graph-based pangenome data, designed to simplify the exploration of complex genetic variation. It currently visualizes data from the HPRC pangenome graph and is demonstrated in use with cystic fibrosis data.https://github.com/ScottMastro/pangyplotpangyplotbiotools:pangyplotv.0.1.0Web applicationhttp://edamontology.org/topic_0622Genomicshttp://edamontology.org/topic_3056Population geneticsJavaScriptPythonMITEmergingFree of chargehttp://edamontology.org/operation_3744Multiple sample visualisationhttp://edamontology.org/operation_3208Genome visualisationhttps://pangyplot.research.sickkids.ca/MirrorLive Instancehttps://zenodo.org/records/17174109RepositoryExample Datahttps://pangyplot.readthedocs.io/en/latest/User manualbubblegunincludes10.1101/2025.10.31.684064Preprintv.0.1.0Scott Mastromatteohttps://orcid.org/0000-0002-3551-2247PersonDeveloperFrogFrog2 (Free Online Drug Conformation 2) is a service aimed at generating 3D conformations for small molecules starting from their 1D, 2D or 3D descriptions (smiles, sdf or mol2 input formats). Frog2 improves upon Frog1 by embedding new energy minimization and ring generation capacities.https://mobyle2.rpbs.univ-paris-diderot.fr/cgi-bin/portal.py#forms::Frog2frog2biotools:frog22.14Web applicationhttp://edamontology.org/topic_2275Molecular modellinghttp://edamontology.org/topic_0154Small moleculesFreewareMatureFree of chargehttp://edamontology.org/operation_3429Generationhttp://edamontology.org/data_1463Small molecule structurehttp://edamontology.org/format_3814SDFhttp://edamontology.org/format_1196SMILEShttp://edamontology.org/format_3816Mol23D generation from 1D/2Dhttps://bioserv.rpbs.univ-paris-diderot.fr/services/Frog2/General10.1093/nar/gkq32520444874PMC2896087PrimaryPierre Tufférypierre.tuffery@univ-paris-diderot.frhttps://orcid.org/0000-0003-1033-9895PersonPrimary contactFrederic Guyonfrederic.guyon@univ-paris-diderot.frPersonPrimary contactMaria A. Mitevamaria.mitev@inserm.frPersonPrimary contactCOPASIOpen-source software application for creating and solving mathematical models of biological processes such as metabolic networks, cell-signaling pathways, regulatory networks, infectious diseases, and many others. It includes features to define models of biological processes, simulate and analyze these models, generate analysis reports, and import/export models in SBML format.http://copasi.org/copasibiotools:copasiCommand-line toolLibraryDesktop applicationhttp://edamontology.org/topic_2259Systems biologyMacLinuxWindowsC++Artistic-2.0de.NBIEBI Training ToolsMatureFree of chargeOpen accessGermanyhttp://edamontology.org/operation_3562Network simulationhttp://edamontology.org/operation_2426Modelling and simulationhttp://edamontology.org/operation_3926Pathway visualisationhttp://edamontology.org/operation_3660Metabolic network modellinghttp://edamontology.org/data_2600Pathway or networkhttp://edamontology.org/format_3686COMBINE OMEXhttp://edamontology.org/format_3685SED-MLhttp://edamontology.org/format_3239CopasiMLhttp://edamontology.org/format_2585SBMLhttps://groups.google.com/g/copasi-user-forumDiscussion forumUser Forumhttp://tracker.copasi.org/Issue trackerIssue trackerhttps://github.com/copasi/COPASIRepositoryGithub Repohttps://fosstodon.org/@copasiSocial mediahttp://copasi.org/Download/BinariesSource and binary packages are available for download.http://copasi.org/Support/User_Manual/User manualcorcusedBypycotoolsusedBybiosimulationsincludedInsbmlwebappusedBylibsbmlusesbasicousedBy10.1093/bioinformatics/btl4851703268310.1007/978-1-59745-525-1_21939943310.1016/j.jbiotec.2017.06.120028655634PMC5623632http://copasi.org/About/Team/PersonPrimary contactFrank T. Bergmannfrank.bergmann@bioquant.uni-heidelberg.dehttps://orcid.org/0000-0001-5553-4702PersonPrimary contactBCFtoolsBCFtools is a set of utilities that manipulate variant calls in the Variant Call Format (VCF) and its binary counterpart BCF. All commands work transparently with both VCFs and BCFs, both uncompressed and BGZF-compressed.http://www.htslib.org/bcftoolsbiotools:bcftools1.01.11.21.31.3.11.41.4.11.51.61.71.81.91.101.10.11.10.21.111.121.131.141.151.15.11.161.171.181.191.201.211.21.11.221.22.11.231.23.1SuiteCommand-line toolhttp://edamontology.org/topic_0199Genetic variationhttp://edamontology.org/topic_2885DNA polymorphismhttp://edamontology.org/topic_3517GWAS studyhttp://edamontology.org/topic_3516Genotyping experimentMacLinuxWindowsCMITBCFtoolsMatureFree of chargeOpen accesshttp://edamontology.org/operation_3227Variant callinghttp://edamontology.org/operation_2409Data handlinghttp://edamontology.org/data_3498Sequence variationshttp://edamontology.org/format_3020BCFhttp://edamontology.org/format_3016VCFMultiple data munging operations.https://github.com/samtools/bcftoolsRepositoryhttp://www.htslib.org/support/#listsMailing listhttps://github.com/samtools/bcftools/issuesIssue trackerhttp://www.htslib.org/download/Downloads pagehttp://www.htslib.org/doc/bcftools.htmlGeneralhttp://www.htslib.org/workflow/#mapping_to_variantOtherA workflow for BCFtools.htslibuses10.1093/bioinformatics/btp35219505943PMC2723002PrimaryThe Sequence Alignment/Map format and SAMtools.10.1093/gigascience/giab00833590861PMC7931819PrimaryTwelve years of SAMtools and BCFtools.Wellcome Sanger Institutesamtools@sanger.ac.ukhttps://www.sanger.ac.uk/InstituteProviderSamtools Help mailing listhttps://lists.sourceforge.net/lists/listinfo/samtools-helpProjectSupportSAMtoolsSAMtools and BCFtools are widely used programs for processing and analysing high-throughput sequencing data. They include tools for file format conversion and manipulation, sorting, querying, statistics, variant calling, and effect analysis amongst other methods.http://www.htslib.org/samtoolsbiotools:samtools1.01.11.21.31.3.11.41.4.11.51.61.71.81.91.101.111.121.131.141.151.15.11.161.16.11.171.181.191.19.11.19.21.201.211.21.11.221.22.11.22.21.231.23.1SuiteCommand-line toolhttp://edamontology.org/topic_0102Mappinghttp://edamontology.org/topic_0080Sequence analysishttp://edamontology.org/topic_3168Sequencinghttp://edamontology.org/topic_3325Rare diseasesMacLinuxWindowsCMITAnimal and Crop GenomicsRare DiseaseSAMtoolsMatureFree of chargeOpen accesshttp://edamontology.org/operation_0227Indexinghttp://edamontology.org/operation_0337Visualisationhttp://edamontology.org/operation_3695Data filteringhttp://edamontology.org/operation_0335Data formattinghttp://edamontology.org/operation_3096Data editinghttp://edamontology.org/operation_1812Data parsinghttp://edamontology.org/operation_3802Data sortinghttp://edamontology.org/data_0924Sequence tracehttp://edamontology.org/format_2572BAMhttp://edamontology.org/format_3462CRAMhttp://edamontology.org/format_2573SAMhttps://github.com/samtools/samtoolsRepositoryhttp://www.htslib.org/support/#listsMailing listhttps://github.com/samtools/samtools/issuesIssue trackerhttp://www.htslib.org/download/Downloads pagehttp://www.htslib.org/doc/#howtosOtherHowTos for samtoolshttp://www.htslib.org/doc/#manual-pagesUser manualhttp://www.htslib.org/download/Installation instructionshtslibuses10.1093/bioinformatics/btp35219505943PMC2723002PrimaryThe Sequence Alignment/Map format and SAMtools.10.1093/gigascience/giab00833590861PMC7931819PrimaryTwelve years of SAMtools and BCFtools.10.1093/bioinformatics/btr50921903627PMC3198575Richard Durbinrd@sanger.ac.ukPersonContributorWellcome Sanger Institutesamtools@sanger.ac.ukhttps://www.sanger.ac.uk/InstituteProviderPrimary contactSamtools Help mailing listhttps://lists.sourceforge.net/lists/listinfo/samtools-helpProjectSupportHTSlibThe main purpose of HTSlib is to provide access to genomic information files, both alignment data (SAM, BAM, and CRAM formats) and variant data (VCF and BCF formats). The library also provides interfaces to access and index genome reference data in FASTA format and tab-delimited files with genomic coordinates. It is utilized and incorporated into both SAMtools and BCFtools.http://www.htslib.org/htslibbiotools:htslib1.01.11.21.2.11.31.3.11.3.21.41.4.11.51.61.71.81.91.101.10.11.10.21.111.121.131.141.151.15.11.161.171.181.191.201.21.11.221.22.11.22.21.231.23.1Libraryhttp://edamontology.org/topic_3071Data managementWindowsLinuxMacCMITAnimal and Crop GenomicsMatureFree of chargeOpen accesshttp://edamontology.org/operation_2409Data handlinghttp://edamontology.org/data_0924Sequence tracehttp://edamontology.org/format_3462CRAMhttp://edamontology.org/format_1929FASTAhttp://edamontology.org/format_2573SAMhttp://edamontology.org/format_2572BAMhttp://edamontology.org/format_1930FASTQhttp://edamontology.org/data_3498Sequence variationshttp://edamontology.org/format_3020BCFhttp://edamontology.org/format_3016VCFhttps://github.com/samtools/htslibRepositoryhttp://www.htslib.org/support/#listsMailing listhttps://github.com/samtools/htslib/issuesIssue trackerhttp://www.htslib.org/download/Downloads pagehttp://www.htslib.org/doc/#manual-pagesUser manualsamtoolsusedBybcftoolsusedBy10.1093/gigascience/giab00733594436PMC7931820PrimaryHTSlib: C library for reading/writing high-throughput sequencing data.Wellcome Sanger Institutesamtools@sanger.ac.ukhttps://www.sanger.ac.uk/InstituteProviderPrimary contactSamtools Help mailing listhttps://lists.sourceforge.net/lists/listinfo/samtools-helpProjectSupportMetaboLinkA web application for Streamlined Processing and Analysis of Large-Scale Untargeted Metabolomics Data.https://computproteomics.bmb.sdu.dk/MetaboLink/metabolinkbiotools:metabolinkWeb applicationhttp://edamontology.org/topic_3172Metabolomicshttp://edamontology.org/topic_0153Lipidomicshttp://edamontology.org/topic_0769WorkflowsMacLinuxWindowsRMITEmergingFree of chargeOpen accesshttp://edamontology.org/operation_3557Imputationhttp://edamontology.org/operation_3435Standardisation and normalisationhttp://edamontology.org/data_2603Expression datahttp://edamontology.org/format_3752CSVhttps://github.com/M3Metabolomics/MetaboLink/Repositoryhttps://github.com/M3Metabolomics/MetaboLink/wikiUser manual10.1093/bioinformatics/btae45939018180PMC11269424PrimaryAna Mendesanamendesml@outlook.comhttps://orcid.org/0009-0008-5170-0927PersonNils J Færgemannils.f@bmb.sdu.dkhttps://orcid.org/0000-0002-9281-5287PersonPrimary contactbiogrowthBiogrowth provides an interface to the biogrowth package for R. It includes functions for describing population growth based on the principles of predictive microbiology. It can be used for making predictions (constant or dynamic environmental conditions; deterministic or dynamic) or model fitting (primary models, one-step primary and secondary models, dynamic models and global models). The whole project is Open Accesss.https://foodlab-upct.shinyapps.io/biogrowth4/biogrowthbiotools:biogrowth1.0.8Web applicationhttp://edamontology.org/topic_3697Microbial ecologyhttp://edamontology.org/topic_3301Microbiologyhttp://edamontology.org/topic_0092Data visualisationhttp://edamontology.org/topic_3569Applied mathematicsGPL-3.0-or-laterMatureFree of chargeOpen accesshttps://foodlab-upct.shinyapps.io/biogrowth4/Servicehttps://github.com/albgarre/biogrowth4Repositoryhttps://github.com/albgarre/biogrowth4Source code10.18637/jss.v107.i01PrimaryGarre, A., Koomen, J., den Besten, H. M. W., & Zwietering, M. H. (2023). Modeling Population Growth in R with the biogrowth Package. Journal of Statistical Software, 107(1), 1–51. https://doi.org/10.18637/jss.v107.i01Freezing-PointFreezing-Point is a user-friendly open-source software for the automated analysis of freezing behavior in rodents. Based on recorded videos or pose estimation files. An adaptive, data-driven algorithm automatically determines freezing detection thresholds, reducing subjective bias while preserving user oversight. Freezing-Point adopts a user-oriented design centered on a graphical interface that provides continuous visual access to original data, processing steps and analysis results. This design enables users to inspect, validate or refine results while minimizing unnecessary data manipulation.https://github.com/gillescourtand/Freezing-PointFreezing-Pointbiotools:Freezing-Point1.0.2Desktop applicationhttp://edamontology.org/topic_3304NeurobiologyMacLinuxWindowsPythonGPL-3.0MatureFree of chargeOpen accesshttp://edamontology.org/operation_3799Quantificationhttp://edamontology.org/operation_0337Visualisationhttp://edamontology.org/operation_2425Optimisation and refinementhttps://github.com/gillescourtand/Freezing-Point/releasesBinaries1.0.2https://github.com/gillescourtand/Freezing-Point/blob/main/Doc/User_guide.mdQuick start guideQUASTQUAST stands for QUality ASsessment Tool.
It evaluates a quality of genome assemblies by computing various metrics and providing nice reports.http://quast.sourceforge.net/quastquastbiotools:quastv.5.3.0Workflowhttp://edamontology.org/topic_0196Sequence assemblyLinuxMacPerlPythonCGPL-2.0ONTeaterMatureFree of chargeOpen accesshttp://edamontology.org/operation_0337Visualisationhttp://edamontology.org/operation_3180Sequence assembly validationhttp://edamontology.org/data_1234Sequence set (nucleic acid)http://edamontology.org/format_1929FASTA# Running quast on a eukaryotic genomequast -ek assembly.fa --out output_prefixhttps://github.com/ablab/quastRepositoryhttps://github.com/ablab/quast/issuesIssue trackerhttp://quast.bioinf.spbau.ru/General10.1093/bioinformatics/btt08623422339PMC3624806QUAST Supportquast.support@cab.spbu.ruPersonPrimary contactEUCAIM Wizard ToolThe EUCAIM Wizard Tool performs an analysis of data re-identification risks of imaging and clinical data that follow the EUCAIM CDM. It includes and uses an EUCAIM specific configuration of the ARX Data Anonymization Tool (biotools:arx), by supporting a wide variety of privacy and risk models as well methods for analyzing the usefulness of output data.https://github.com/cbml-forth/eucaim_wizard_tooleucaim_wizard_toolbiotools:eucaim_wizard_toolbeta1.0Desktop applicationhttp://edamontology.org/topic_3384Medical imaginghttp://edamontology.org/topic_4044Data protectionhttp://edamontology.org/topic_2640OncologyMacLinuxWindowsJavaEUPL-1.2EUCAIMEmergingFree of chargeOpen accesshttp://edamontology.org/operation_3283Anonymisationhttps://github.com/cbml-forth/eucaim_wizard_toolRepositoryhttps://docs.google.com/document/d/1pi-7SvDKzVSYS78MhvnBX7PcXF3kZAc6/edit?usp=sharing&ouid=115998150174651530097&rtpof=true&sd=trueUser manualarxincludesarxusesComputational BioMedicine Laboratory, Foundation for Research and Technology Hellas (FORTH)https://www.ics.forth.gr/cbml/?lang=enInstituteProviderIntercranial Meningioma SegmenterThe Intercranial Meningioma Segmenter is a software tool developed by researchers from Universidad Politécnica de Madrid and Children’s National Hospital for the segmentation and analysis of intercranial meningiomas in magnetic resonance imaging (MRI). Built in Python, it enables precise quantitative analysis of intercranial meningiomas in brain MRI scans to support clinical decision-making in both diagnosis and prognosis.https://github.com/BIT-UPM/EUCAIM/tree/main/intercranial_meningioma_segmenterintercranial_meningioma_segmenterbiotools:intercranial_meningioma_segmenterv1.0WorkflowWeb applicationCommand-line toolhttp://edamontology.org/topic_3444MRIhttp://edamontology.org/topic_3474Machine learningWindowsLinuxMacPythonCC-BY-NC-ND-4.0EUCAIMMatureFree of chargeOpen accesshttp://edamontology.org/operation_3553Image annotationhttps://segmenter.hope4kids.io/OtherMain app webpagehttps://github.com/Pediatric-Accelerated-Intelligence-Lab/HOPE-Segmenter-KidsRepositoryGitHub repositoryhttps://docs.hope4kids.io/HOPE-Segmenter-Kids/API documentationCitation instructionsTerms of useCode of conductRelease notesUser manualGeneralQuick start guide10.1007/978-3-031-76163-8_2010.1109/ISBI56570.2024.1063546910.48550/arXiv.2412.0409410.48550/arXiv.2412.04111Daniel Capellán-Martíndaniel.capellan@upm.eshttps://orcid.org/0000-0002-9743-0845Primary contactDeveloperContributorSupportAbhijeet Paridapabhijeet@childrensnational.orghttps://orcid.org/0000-0002-4978-0576DeveloperContributorSupportMaintainerZhifan Jiangzjiang@childrensnational.orgContributorDeveloperSupportMaría Jesus Ledesma-Carbayomj.ledesma@upm.eshttps://orcid.org/0000-0001-6846-3923Primary contactContributorMarius George Lingurarumlingura@childrensnational.orgPrimary contactContributorBrain Metastasis SegmenterThe Brain Metastasis Segmenter is a software tool developed by researchers from Universidad Politécnica de Madrid and Children’s National Hospital for the segmentation and analysis of brain metastases in magnetic resonance imaging (MRI). Built in Python, it enables precise quantitative analysis of brain metastases in MRI scans to support clinical decision-making in both diagnosis and prognosis.https://github.com/BIT-UPM/EUCAIM/tree/main/brain_metastasis_segmenterbrain_metastasis_segmenterbiotools:brain_metastasis_segmenterv1.0Command-line toolWeb applicationWorkflowhttp://edamontology.org/topic_3444MRIhttp://edamontology.org/topic_3474Machine learningWindowsMacLinuxPythonCC-BY-NC-ND-4.0EUCAIMMatureFree of chargeOpen accesshttp://edamontology.org/operation_3553Image annotationhttps://segmenter.hope4kids.io/OtherMain app webpagehttps://github.com/Pediatric-Accelerated-Intelligence-Lab/HOPE-Segmenter-KidsRepositoryGitHub repositoryhttps://docs.hope4kids.io/HOPE-Segmenter-Kids/API documentationCitation instructionsTerms of useCode of conductRelease notesUser manualGeneralQuick start guide10.1007/978-3-031-76163-8_2010.1109/ISBI56570.2024.1063546910.48550/arXiv.2412.0409410.48550/arXiv.2412.04111Daniel Capellán-Martíndaniel.capellan@upm.eshttps://orcid.org/0000-0002-9743-0845Primary contactDeveloperContributorSupportAbhijeet Paridapabhijeet@childrensnational.orghttps://orcid.org/0000-0002-4978-0576DeveloperContributorSupportMaintainerZhifan Jiangzjiang@childrensnational.orgContributorDeveloperSupportMaría Jesus Ledesma-Carbayomj.ledesma@upm.eshttps://orcid.org/0000-0001-6846-3923Primary contactContributorMarius George Lingurarumlingura@childrensnational.orgPrimary contactContributorSub-Saharan Africa Brain Glioma SegmenterThe Sub-Saharan Africa Brain Glioma Segmenter is a software tool developed by researchers from Universidad Politécnica de Madrid and Children’s National Hospital for the segmentation and analysis of intercranial meningiomas in magnetic resonance imaging (MRI). Built in Python, it enables precise quantitative analysis of gliomas in brain MRI scans to support clinical decision-making in both diagnosis and prognosis. This tool was trained on a cohort of patients from Sub-Saharan Africa.https://github.com/BIT-UPM/EUCAIM/tree/main/sub_saharan_africa_brain_glioma_segmentersub-saharan_africa_brain_glioma_segmenterbiotools:sub-saharan_africa_brain_glioma_segmenterv1.0WorkflowWeb applicationCommand-line toolhttp://edamontology.org/topic_3444MRIhttp://edamontology.org/topic_3474Machine learningLinuxMacWindowsPythonCC-BY-NC-ND-4.0EUCAIMMatureFree of chargeOpen accesshttp://edamontology.org/operation_3553Image annotationhttps://segmenter.hope4kids.io/OtherMain app webpagehttps://github.com/Pediatric-Accelerated-Intelligence-Lab/HOPE-Segmenter-KidsRepositoryGitHub repositoryhttps://docs.hope4kids.io/HOPE-Segmenter-Kids/API documentationCitation instructionsTerms of useCode of conductRelease notesUser manualGeneralQuick start guide10.1007/978-3-031-76163-8_2010.1109/ISBI56570.2024.1063546910.48550/arXiv.2412.0409410.48550/arXiv.2412.04111Daniel Capellán-Martíndaniel.capellan@upm.eshttps://orcid.org/0000-0002-9743-0845Primary contactDeveloperContributorSupportAbhijeet Paridapabhijeet@childrensnational.orghttps://orcid.org/0000-0002-4978-0576DeveloperContributorSupportMaintainerZhifan Jiangzjiang@childrensnational.orgContributorDeveloperSupportMaría Jesus Ledesma-Carbayomj.ledesma@upm.eshttps://orcid.org/0000-0001-6846-3923Primary contactContributorMarius George Lingurarumlingura@childrensnational.orgPrimary contactContributorBrain Glioma SegmenterThe Brain Glioma Segmenter is a software tool developed by researchers from Universidad Politécnica de Madrid and Children’s National Hospital for the segmentation and analysis of brain gliomas in magnetic resonance imaging (MRI). Built in Python, it enables precise quantitative analysis of brain gliomas in MRI scans to support clinical decision-making in both diagnosis and prognosis.https://github.com/BIT-UPM/EUCAIM/tree/main/brain_glioma_segmenterbrain_glioma_segmenterbiotools:brain_glioma_segmenterv1.0Command-line toolWeb applicationWorkflowhttp://edamontology.org/topic_3444MRIhttp://edamontology.org/topic_3474Machine learningWindowsMacLinuxPythonCC-BY-NC-ND-4.0EUCAIMMatureFree of chargeOpen accesshttp://edamontology.org/operation_3553Image annotationhttps://segmenter.hope4kids.io/OtherMain app webpagehttps://github.com/Pediatric-Accelerated-Intelligence-Lab/HOPE-Segmenter-KidsRepositoryGitHub repositoryhttps://docs.hope4kids.io/HOPE-Segmenter-Kids/API documentationCitation instructionsTerms of useCode of conductRelease notesUser manualGeneralQuick start guide10.1007/978-3-031-76163-8_2010.1109/ISBI56570.2024.1063546910.48550/arXiv.2412.0409410.48550/arXiv.2412.04111Daniel Capellán-Martíndaniel.capellan@upm.eshttps://orcid.org/0000-0002-9743-0845Primary contactContributorDeveloperSupportAbhijeet Paridapabhijeet@childrensnational.orghttps://orcid.org/0000-0002-4978-0576ContributorDeveloperSupportMaintainerZhifan Jiangzjiang@childrensnational.orgContributorDeveloperSupportMaría Jesus Ledesma-Carbayomj.ledesma@upm.eshttps://orcid.org/0000-0001-6846-3923Primary contactContributorMarius George Lingurarumlingura@childrensnational.orgPrimary contactContributorPediatric Brain Tumor SegmenterThe Pediatric Brain Tumor Segmenter is a software tool developed by researchers from Universidad Politécnica de Madrid and Children’s National Hospital for the segmentation and analysis of pediatric brain tumors in magnetic resonance imaging (MRI). Built in Python, it enables precise quantitative analysis of pediatric brain tumors in MRI scans to support clinical decision-making in both diagnosis and prognosis.https://github.com/BIT-UPM/EUCAIM/tree/main/pediatric_brain_tumor_segmenterpediatric_brain_tumor_segmenterbiotools:pediatric_brain_tumor_segmenterv1.0Command-line toolWeb applicationWorkflowhttp://edamontology.org/topic_3444MRIhttp://edamontology.org/topic_3474Machine learningWindowsMacLinuxPythonCC-BY-NC-SA-4.0EUCAIMMatureFree of chargeOpen accesshttp://edamontology.org/operation_3553Image annotationhttps://segmenter.hope4kids.io/OtherMain app webpagehttps://github.com/Pediatric-Accelerated-Intelligence-Lab/HOPE-Segmenter-KidsRepositoryGitHub repositoryhttps://docs.hope4kids.io/HOPE-Segmenter-Kids/API documentationCitation instructionsTerms of useCode of conductRelease notesUser manualGeneralQuick start guide10.1007/978-3-031-76163-8_2010.1109/ISBI56570.2024.1063546910.48550/arXiv.2412.0409410.48550/arXiv.2412.04111Daniel Capellán-Martíndaniel.capellan@upm.eshttps://orcid.org/0000-0002-9743-0845PersonPrimary contactDeveloperContributorSupportAbhijeet Paridapabhijeet@childrensnational.orghttps://orcid.org/0000-0002-4978-0576DeveloperContributorSupportMaintainerZhifan Jiangzjiang@childrensnational.orgContributorDeveloperSupportMaría Jesus Ledesma-Carbayomj.ledesma@upm.eshttps://orcid.org/0000-0001-6846-3923Primary contactContributorMarius George Lingurarumlingura@childrensnational.orgPrimary contactContributorWEBnmaWEBnm@ 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_1476PDBConstructs 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_1476PDBPerforms 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, NorwayInstituteProviderUiBInstituteProviderBioMercatorBioMercator is a software that provides a complete set of algorithms and visualization tool covering all steps required to perform QTL meta-analysis, graphical representation of large datasets. User may import sequence and genome annotations datasets within the software in order to display functional annotation related to QTL and meta-QTL.https://sourcesup.renater.fr/projects/biomercatorBioMercatorbiotools:BioMercator4.2.3Desktop applicationhttp://edamontology.org/topic_3055Quantitative geneticshttp://edamontology.org/topic_0780Plant biologyLinuxWindowsMacJavaGPL-3.0MatureFree of chargehttp://edamontology.org/operation_0282Genetic mappinghttp://edamontology.org/operation_2944Physical mappinghttp://edamontology.org/data_1860QTL maphttp://edamontology.org/format_2332XMLhttp://edamontology.org/format_2330Textual formathttp://edamontology.org/data_1288Genome maphttp://edamontology.org/format_1975GFF3https://sourcesup.renater.fr/frs/?group_id=2301Binaries4.2.310.1093/bioinformatics/bth230150598203SERtoolDetection of Sequence-Enriched Regions (SER) in Proteins and Nucleic Acidshttps://github.com/rennmeng/SERtoolsertoolbiotools:sertool1.0.1Bioinformatics portalWeb serviceCommand-line toolhttp://edamontology.org/topic_0080Sequence analysishttp://edamontology.org/topic_0160Sequence sites, features and motifsLinuxRustPythonMITLegacyFree of chargeOpen accesshttp://edamontology.org/operation_0291Sequence clusteringIndependent scan for 20 amino acidspython SERtool.py A,C,D,E,F,G,H,I,K,L,M,N,P,Q,R,S,T,V,W,Y --input test.fasta --start 20 --point 18 20 30 50http://edamontology.org/operation_0291Sequence clusteringSame class D-E analysispython SERtool.py D-E --input test.fasta --start 20 --point 18 20 30 50http://edamontology.org/operation_0291Sequence clusteringWildcard: all X-S motifs (e.g., DS, RS)python SERtool.py .S --input test.fasta --start 15 --point 5 10 10 30https://github.com/rennmeng/SERtoolRepositoryhttps://www.sertool.net/Servicehttps://www.sertool.net/resourceDownloads page1.0.1https://www.sertool.net/helpUser manualMeng Renrennmeng@smail.nju.edu.cnRMSX and FlipbookRMSX + Flipbook is a molecular dynamics analysis and visualization tool for generating residue-resolved structural motion summaries from simulation trajectories. It computes per-residue motion metrics and produces color- and thickness-encoded protein snapshots arranged as static flipbook panels or interactive displays for publication, presentation, and exploratory analysis.https://github.com/AntunesLab/rmsxrmsx_and_flipbookbiotools:rmsx_and_flipbookSuiteWorkflowhttp://edamontology.org/topic_3306Biophysicshttp://edamontology.org/topic_3307Computational biologyhttp://edamontology.org/topic_3332Computational chemistryhttp://edamontology.org/topic_0176Molecular dynamicsMacLinuxWindowsRPythonMITFree of chargeOpen accesshttp://edamontology.org/operation_3890Trajectory visualizationhttp://edamontology.org/data_3870Trajectory datarun_rmsx_flipbookchimeraxusesmdanalysisuses10.1038/s41598-026-39869-741720904PrimaryMaplerMapler is a pipeline for assessing assembly quality in taxonomically rich metagenomes sequenced with HiFi reads. It incorporates state-of-the-art metrics and facilitates the comparison of assembly strategies.https://github.com/Nimauric/Maplermaplerbiotools:maplerWorkflowCommand-line toolhttp://edamontology.org/topic_3174Metagenomicshttp://edamontology.org/topic_0196Sequence assemblyBashPythonAGPL-3.0Free of chargeOpen accesshttp://edamontology.org/operation_0310Sequence assemblyhttp://edamontology.org/data_0924Sequence tracehttp://edamontology.org/format_1930FASTQhttp://edamontology.org/operation_3180Sequence assembly validationhttp://edamontology.org/operation_3731Sample comparisonhttp://edamontology.org/data_1234Sequence set (nucleic acid)http://edamontology.org/format_1929FASTAhttp://edamontology.org/operation_3798Read binninghttp://edamontology.org/data_1234Sequence set (nucleic acid)http://edamontology.org/format_1929FASTAhttps://github.com/Nimauric/MaplerRepository10.1093/BIOINFORMATICS/BTAF33440478660PMC12205171Nicolas Mauricenicolas.maurice@inria.frhttps://orcid.org/0009-0009-9615-2765PersonClaire Lemaitrehttps://orcid.org/0000-0001-8675-170XRiccardo Vicedominihttps://orcid.org/0000-0002-7706-0998Clémence Friouxclemence.frioux@inria.frhttps://orcid.org/0000-0003-2114-0697PersonHistoAtlasA pan-cancer morphology atlas linking histological features to molecular and clinical outcomeshttps://histoatlas.comhistoatlasbiotools:histoatlasWeb applicationBioinformatics portalDatabase portalhttp://edamontology.org/topic_0091BioinformaticsCC-BY-NC-4.0Free of chargeOpen accesshttp://edamontology.org/operation_2436Gene-set enrichment analysishttps://github.com/HistoAtlas/HistoAtlasRepositoryhttps://histoatlas.com/methods/GeneralMethodologySTaBioM-Standardised-Bioinformatics-for-Microbial-samplesA unified CLI + GUI for running microbiome analysis pipelines on long-read and short-read sequencing data, supporting both 16S amplicon and shotgun metagenomics workflows for all DNA sequencing technologies.https://github.com/izzydavidson/STaBioM-Standardised-Bioinformatics-for-Microbial-samples.gitSTaBioM-stabiom-standardised-bioinformatics-for-microbial-samplesbiotools:STaBioM-stabiom-standardised-bioinformatics-for-microbial-samplesbetav1Web applicationCommand-line toolhttp://edamontology.org/topic_3673Whole genome sequencinghttp://edamontology.org/topic_3673Whole genome sequencingMacLinuxWindowsShellPythonRFreewareEmergingFree of chargeOpen accesshttp://edamontology.org/operation_3460Taxonomic classificationhttps://github.com/izzydavidson/STaBioM-Standardised-Bioinformatics-for-Microbial-samples.gitRepositoryhttps://github.com/izzydavidson/STaBioM-Standardised-Bioinformatics-for-Microbial-samples.gitSource codeDownload whole repo to allow for both CLI and GUI usageV1https://github.com/izzydavidson/STaBioM-Standardised-Bioinformatics-for-Microbial-samples.gitGeneralsplithalfrEstimates split-half reliabilities for scoring algorithms of cognitive tasks and questionnaireshttps://github.com/tpronk/splithalfrsplithalfrbiotools:splithalfrLibraryhttp://edamontology.org/topic_0003TopicRLGPL-3.0-or-laterMatureFree of chargeOpen accesshttps://github.com/tpronk/splithalfrRepositoryhttps://cran.r-project.org/package=splithalfrSoftware packagehttps://github.com/tpronk/splithalfr/blob/main/README.mdQuick start guide10.3758/s13423-021-01948-334100223PMC8858277PrimaryThomas Pronkt.pronk1@amsterdamumc.nlhttps://orcid.org/0000-0001-9334-7190PersonRandom Number LabAn interactive set of tools including randomization of data (even stratified random sampling) and random assignments for studies, generation of random numbers following specific probability distributions, generation of random and quasi-random point distributions and sampling patterns, noise in one or two dimensions with adjustable spectral properties, random walks and Lévy flights. Own data tables can be provided for random sampling in a privacy-friendly way, as data processing takes place directly in the browser and no data is transferred to anywhere else. The Random Number Lab also offers some educational material and worksheets and can be used for scientific and educational purposes.https://randomnumberlab.orgrandom_number_labbiotools:random_number_labRRID:SCR_028010rridWeb applicationhttp://edamontology.org/topic_2269Statistics and probabilityhttp://edamontology.org/topic_3678Experimental design and studiesLinuxiOSMacAndroidWindowsJavaScriptMatureFree of chargehttp://edamontology.org/operation_0364Random sequence generationGeneration of sequences of random numbers or elements, spatial point patterns, random walkshttp://edamontology.org/operation_0337VisualisationVisualization of random distributions and random processeshttp://edamontology.org/operation_2409Data handlingRandomization and permutation of data in a privacy-preserving wayThomas Amthorhello@randomnumberlab.orghttps://orcid.org/0000-0002-1456-6131PersonDeveloperMaintainerPLASTPLAST is a heuristical method to search for highest scoring local alignments between a DNA sequence query and a graphical pangenome. It takes as input a plain DNA sequence and a pangenome which may either be a set of (multiple) FASTA or FASTQ files or a sequence graph constructed by the tool Bifrost. It then outputs statistically meaningful (gapped) alignments in the style of the NCBI BLAST standard output format. Alignments are calculated based on a "seed-and-extend approach" while traversing the sequence graph. Biologically meaningful alignments are filtered by using an alignment statistic explicitly developed for sequence-to-graph alignments involving graphical pangenomes.https://github.com/tischulz1/plastpangenome-blastbiotools:pangenome-blast0.0.1-0.2.0Command-line toolhttp://edamontology.org/topic_0797Comparative genomicshttp://edamontology.org/topic_0080Sequence analysisLinuxMacWindowsC++GPL-3.0MatureFree of chargeOpen accesshttp://edamontology.org/operation_0495Local alignmenthttp://edamontology.org/data_3494DNA sequencehttp://edamontology.org/format_1211unambiguous pure nucleotidehttp://edamontology.org/data_1234Sequence set (nucleic acid)http://edamontology.org/format_3975GFA 1http://edamontology.org/format_2333Binary formatIn order to search for alignments within the pangenome graph,
A pangenome graph used to search for alignments consists of (1) a file in GFA format containing all sequences of the graph, (2) a binary file produced by the tool itself or the software "Bifrost" and (3) a program-specific index data structure in binary format.PLAST Search -i pangenomeGraphCommonFilePrefix -q fileContainingOneQueryPerLinehttp://edamontology.org/operation_0227Indexinghttp://edamontology.org/data_0850Sequence sethttp://edamontology.org/format_1929FASTAhttp://edamontology.org/format_1930FASTQIf a pangenome graph already exists and only an index has to be built, FASTA/FASTQ files are not needed.PLAST Build -i pangenomeGraphCommonFilePrefix -R *.fastahttps://gitlab.ub.uni-bielefeld.de/gi/plastRepositoryhttps://github.com/tischulz1/plastMirrorhttps://gitlab.ub.uni-bielefeld.de/gi/plast/-/blob/master/README.mdGeneral10.1093/bioinformatics/btab07733532821PMC8388040PrimaryMethodBenchmarking studyBielefeld Universityhttps://www.uni-bielefeld.de/InstituteProviderGenome Informaticshttps://gi.cebitec.uni-bielefeld.de/InstituteProviderTizian Schulzplast-service@cebitec.uni-bielefeld.dehttps://orcid.org/0000-0003-0744-7078PersonDeveloperFANTASIAFANTASIA (Functional ANnoTAtion based on embedding space SImilArity) is a pipeline for protein annotating via GO term transference using the embedding space. FANTASIA’s latest developments include additional protein language models and provide enhanced functionalities.https://github.com/CBBIO/fantasiav2biotools:fantasiav24.0LITECommand-line toolhttp://edamontology.org/topic_3945Molecular evolutionhttp://edamontology.org/topic_0218Natural language processinghttp://edamontology.org/topic_0085Functional genomicshttp://edamontology.org/topic_4010Open scienceLinuxPythonSQLMITMatureFree of chargeOpen accessTools3D-BioInfoProteomicsSpainhttp://edamontology.org/operation_3672Gene functional annotationhttps://github.com/CBBIO/FANTASIARepositoryMain repository contains documentation from latest versionhttps://github.com/MetazoaPhylogenomicsLab/FANTASIARepositoryMain repository contains documentation from linitial version based on Bioembeddings implementation.https://www.earthbiogenome.org/report-on-annotation-recommended-toolsSoftware catalogueRecommended tool for the Earth Biogenome Projecthttps://github.com/CBBIO/FANTASIA-LiteSoftware catalogueThis is the LITE version of FANTASIA for a quick and custom annotationhttps://gitlab.com/ifb-elixirfr/cluster/tools/-/tree/master/tools/fantasia/0.1.0?ref_type=headsRepositoryThis is a repository for FANTASIA-LITE available in Elixir Francehttps://fantasia.readthedocs.io/en/latest/GeneralFull documetnation with user cases, benchmarking, and cluster implementations10.1093/nargab/lqae078Usage10.1007/978-1-0716-4623-6_840601255Method2.8.0This protocol describes the use of the first version of FANTASIA10.1038/s42003-025-08651-240813894PMC12354702Primary4.0Application of FANTASIA to annotate 24 million of genes of 1000 animal speciesFrancisco Miguel Pérez Canalesfmpercan@upo.eshttp://www.bioinfocb.es/PersonPrimary contactDeveloperDocumentorMaintainerSupportProviderProgrammerAna M Rojas Mendozaa.rojas.m@csic.eshttp://www.bioinfocb.es/PersonPrimary contactContributorDocumentorSupportScientific concept and functionalitiesRosa Fernandezrosa.fernandez@ibe.upf-csic.eshttps://www.metazomics.com/ContributorDocumentorScientific concept and functionalitiesFrancisco J. Ruiz Motafraruimot@alum.us.eshttp://www.bioinfocb.es/PersonDeveloperJunior developerGemma Martinez Redondogemma.martinez@ibe.upf-csic.eshttps://www.metazomics.com/PersonContributorDeveloperContributed as developer of the first version of FANTASIA V1Alex Dominguez Rodriguezadomrod4@upo.eshttp://www.bioinfocb.es/PersonDeveloperPrimary contactMaintainerDocumentorImplemented the LITE version of FANTASIAPoly PipelineA data analysis pipeline for Spatial Transcriptomics data tailored to polyploid organisms.https://github.com/capuccino26/POLY_PIPELINEpoly_pipelinebiotools:poly_pipelinev1.0.0doi:10.5281/zenodo.18655692doiv1.0.0Command-line toolScripthttp://edamontology.org/topic_3170RNA-SeqLinuxRBashPythonMITMatureFree of chargeOpen accessToolsPlant Scienceshttp://edamontology.org/operation_0313Expression profile clusteringhttp://edamontology.org/data_3917Count matrixClustering of GEF files.ANALYSIS=1http://edamontology.org/operation_3925Network visualisationhttp://edamontology.org/data_3917Count matrixGeneration of Nodes and Edges.ANALYSIS=3http://edamontology.org/operation_0336Format validationhttp://edamontology.org/data_3112Gene expression matrixData converter.ANALYSIS=0http://edamontology.org/operation_3800RNA-Seq quantificationhttp://edamontology.org/data_3112Gene expression matrixGeneration of count matrix.ANALYSIS=1http://edamontology.org/operation_3695Data filteringhttp://edamontology.org/data_3112Gene expression matrixFiltering of GEF files.ANALYSIS=1https://github.com/capuccino26/POLY_PIPELINERepositoryGithub Repositoryhttps://zenodo.org/records/18655692OtherZenodo Inserthttps://github.com/capuccino26/POLY_PIPELINE/releases/tag/v1.0.0Source codeGithub Releasev1.0.0https://github.com/capuccino26/POLY_PIPELINE#poly_pipelineUser manualGithub Documentation10.5281/zenodo.18655692Otherv1.0.0Zenodo InsertionPedro Cristovão Carvalhopccrvl@gmail.comhttps://cafinvest.com.br/resume.phphttps://orcid.org/0000-0001-9242-6911PersonDeveloperPrimary contactMaintainerProviderSupportMain developer of the pipelineopen-cravatOpenCRAVAT is a new open source, scalable decision support system to support variant and gene prioritization. It offers a dynamic GUI, allowing users to easily, download tools from an extensive resource catalog, create customized pipelines, run jobs at speeds that exceed current variant annotation API services, and explore results in a richly detailed viewing environment. OpenCRAVAT is distinguished from similar tools by the amount and diversity of data resources and computational prediction methods available, which span germline, somatic, common, rare, coding and non-coding variants. We have designed the OpenCRAVAT resource catalog to be open and modular to maximize community and developer involvement, and as a result the catalog is being actively developed and growing larger every month.https://opencravat.orgopen-cravatbiotools:open-cravat2.16.02.17.0Web APIWeb applicationCommand-line toolhttp://edamontology.org/topic_2640Oncologyhttp://edamontology.org/topic_3175Structural variationhttp://edamontology.org/topic_0769Workflowshttp://edamontology.org/topic_0622Genomicshttp://edamontology.org/topic_0625Genotype and phenotypehttp://edamontology.org/topic_3325Rare diseaseshttp://edamontology.org/topic_0080Sequence analysishttp://edamontology.org/topic_0199Genetic variationhttp://edamontology.org/topic_3673Whole genome sequencinghttp://edamontology.org/topic_3676Exome sequencinghttp://edamontology.org/topic_0659Functional, regulatory and non-coding RNAMacLinuxWindowsPythonMITRare DiseaseRare diseaseMatureFree of chargeOpen accesshttp://edamontology.org/operation_3227Variant callinghttp://edamontology.org/operation_3661SNP annotationhttp://edamontology.org/operation_0331Variant effect predictionhttp://edamontology.org/operation_3197Genetic variation analysishttp://edamontology.org/operation_3672Gene functional annotationhttp://edamontology.org/operation_3226Variant prioritisationhttp://edamontology.org/data_3498Sequence variationshttp://edamontology.org/format_3016VCFAdditional input formats include: list of dbSNP rsIDs, HGVS annotation, and a tab-separated variant annotation format.
Output is also in text, excel, and a SQLite database. The SQLIte database format can be loaded into `oc gui` as an interactive web applicationoc run -a ANNOTATOR_LIST input.vcfhttps://run.opencravat.org/ServiceWeb server for running the current version of OpenCRAVAT without needing a local installation.https://github.com/KarchinLab/open-cravatRepositoryhttps://run.opencravat.org/submit/nocache/index.htmlSoftware catalogueCatalogue of modules for OpenCRAVAT, including annotators, variant effect predictors, etc.https://github.com/KarchinLab/open-cravat/releases/Downloads pagehttps://hub.docker.com/r/karchinlab/opencravatContainer filehttps://docs.opencravat.org/en/latest/index.htmlGeneralAPI documentationInstallation instructionsQuick start guideUser manual10.1200/cci.19.0013232228266PMC7113103Kymberleigh A PagelRick KimKyle MoadRachel Karchin