count: 245 list: - accessibility: Open access additionDate: '2017-03-13T17:04:55Z' biotoolsCURIE: biotools:edgar biotoolsID: edgar collectionID: - RD-connect - Rare Disease - Bologna Biocomputing Group community: null confidence_flag: tool cost: Free of charge credit: - email: giulia.babbi3@unibo.it fundrefid: null gridid: null name: Giulia Babbi note: null orcidid: null rorid: null typeEntity: Person typeRole: - Primary contact url: null - email: null fundrefid: null gridid: null name: ELIXIR-ITA-BOLOGNA note: null orcidid: null rorid: null typeEntity: Institute typeRole: - Primary contact url: http://biocomp.unibo.it/ description: A database of Disease-Gene Associations with annotated Relationships among genes. documentation: - note: null type: - User manual url: http://edgar.biocomp.unibo.it/gene_disease_db/tutorial.html download: [] editPermission: authors: - ELIXIR-EE - lmatalonga type: group elixirCommunity: - Rare Diseases elixirNode: - Italy elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: - data: term: Disease name uri: http://edamontology.org/data_3668 format: - term: Textual format uri: http://edamontology.org/format_2330 note: For each heterogeneous or polygenic disease, eDGAR provides information on the relationship among the proteins encoded by the involved genes. operation: - term: Database comparison uri: http://edamontology.org/operation_3561 - term: Genetic variation analysis uri: http://edamontology.org/operation_3197 - term: Pathway or network analysis uri: http://edamontology.org/operation_2497 - term: Gene functional annotation uri: http://edamontology.org/operation_3672 - term: Protein interaction network analysis uri: http://edamontology.org/operation_0276 output: - data: term: Disease report uri: http://edamontology.org/data_1622 format: - term: CSV uri: http://edamontology.org/format_3752 - term: HTML uri: http://edamontology.org/format_2331 - cmd: null input: - data: term: OMIM ID uri: http://edamontology.org/data_1153 format: - term: Textual format uri: http://edamontology.org/format_2330 note: For each heterogeneous or polygenic disease, eDGAR provides information on the relationship among the proteins encoded by the involved genes. operation: - term: Database comparison uri: http://edamontology.org/operation_3561 - term: Pathway or network analysis uri: http://edamontology.org/operation_2497 output: - data: term: Disease report uri: http://edamontology.org/data_1622 format: - term: CSV uri: http://edamontology.org/format_3752 - term: HTML uri: http://edamontology.org/format_2331 homepage: http://edgar.biocomp.unibo.it homepage_status: 0 language: - JavaScript lastUpdate: '2024-03-14T13:58:52.828991Z' license: CC-BY-4.0 link: [] maturity: Mature name: eDGAR operatingSystem: - Linux - Windows - Mac otherID: - type: doi value: doi:10.25504/FAIRsharing.29EHM2 version: null owner: ELIXIR-ITA-BOLOGNA publication: - doi: 10.1186/s12864-017-3911-3 metadata: abstract: 'Background: Genetic investigations, boosted by modern sequencing techniques, allow dissecting the genetic component of different phenotypic traits. These efforts result in the compilation of lists of genes related to diseases and show that an increasing number of diseases is associated with multiple genes. Investigating functional relations among genes associated with the same disease contributes to highlighting molecular mechanisms of the pathogenesis. Results: We present eDGAR, a database collecting and organizing the data on gene/disease associations as derived from OMIM, Humsavar and ClinVar. For each disease-associated gene, eDGAR collects information on its annotation. Specifically, for lists of genes, eDGAR provides information on: i) interactions retrieved from PDB, BIOGRID and STRING; ii) co-occurrence in stable and functional structural complexes; iii) shared Gene Ontology annotations; iv) shared KEGG and REACTOME pathways; v) enriched functional annotations computed with NET-GE; vi) regulatory interactions derived from TRRUST; vii) localization on chromosomes and/or co-localisation in neighboring loci. The present release of eDGAR includes 2672 diseases, related to 3658 different genes, for a total number of 5729 gene-disease associations. 71% of the genes are linked to 621 multigenic diseases and eDGAR highlights their common GO terms, KEGG/REACTOME pathways, physical and regulatory interactions. eDGAR includes a network based enrichment method for detecting statistically significant functional terms associated to groups of genes. Conclusions: eDGAR offers a resource to analyze disease-gene associations. In multigenic diseases genes can share physical interactions and/or co-occurrence in the same functional processes. eDGAR is freely available at: edgar. biocomp.unibo.it.' authors: - name: Babbi G. - name: Martelli P.L. - name: Profiti G. - name: Bovo S. - name: Savojardo C. - name: Casadio R. citationCount: 45 date: '2017-01-01T00:00:00Z' journal: BMC Genomics title: 'eDGAR: A database of disease-gene associations with annotated relationships among genes' note: null pmcid: null pmid: null type: - Primary version: null relation: [] toolType: - Web application - Database portal topic: - term: Pathology uri: http://edamontology.org/topic_0634 - term: Human genetics uri: http://edamontology.org/topic_3574 - term: Rare diseases uri: http://edamontology.org/topic_3325 validated: 1 version: [] - accessibility: Open access additionDate: '2016-05-04T15:36:53Z' biotoolsCURIE: biotools:inps-md biotoolsID: inps-md collectionID: - Rare Disease - Bologna Biocomputing Group community: null confidence_flag: null cost: Free of charge credit: - email: null fundrefid: null gridid: null name: ELIXIR-ITA-BOLOGNA note: null orcidid: null rorid: null typeEntity: Institute typeRole: - Provider url: http://www.biocomp.unibo.it - email: savojard@biocomp.unibo.it fundrefid: null gridid: null name: Castrense Savojardo note: null orcidid: https://orcid.org/0000-0002-7359-0633 rorid: null typeEntity: Person typeRole: - Developer url: null - email: piero.fariselli@unito.it fundrefid: null gridid: null name: Piero Fariselli note: null orcidid: null rorid: null typeEntity: Person typeRole: - Primary contact url: null - email: savojard@biocomp.unibo.it fundrefid: null gridid: null name: Castrense Savojardo note: null orcidid: https://orcid.org/0000-0002-7359-0633 rorid: null typeEntity: Person typeRole: - Primary contact url: http://biocomp.unibo.it/savojard/ description: Predicting the impact of mutations on protein stability from sequence and structure. documentation: - note: null type: - General url: https://inpsmd.biocomp.unibo.it/inpsSuite download: [] editPermission: authors: - ELIXIR-ITA-BOLOGNA - savo type: group elixirCommunity: - 3D-BioInfo elixirNode: - Italy elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: - data: term: Protein sequence (raw) uri: http://edamontology.org/data_2974 format: - term: FASTA uri: http://edamontology.org/format_1929 note: Prediction of the impact of non-synonymous polymorphisms on protein stability from sequence. operation: - term: Protein sequence analysis uri: http://edamontology.org/operation_2479 - term: Genetic variation analysis uri: http://edamontology.org/operation_3197 output: - data: term: Protein report uri: http://edamontology.org/data_0896 format: - term: HTML uri: http://edamontology.org/format_2331 - cmd: null input: - data: term: Protein structure uri: http://edamontology.org/data_1460 format: - term: PDB uri: http://edamontology.org/format_1476 - data: term: Polypeptide chain ID uri: http://edamontology.org/data_1008 format: - term: Textual format uri: http://edamontology.org/format_2330 note: Prediction of the impact of non-synonymous polymorphisms on protein stability from structure. operation: - term: Protein structure analysis uri: http://edamontology.org/operation_2406 - term: Genetic variation analysis uri: http://edamontology.org/operation_3197 output: - data: term: Protein report uri: http://edamontology.org/data_0896 format: - term: HTML uri: http://edamontology.org/format_2331 - data: term: Protein structure uri: http://edamontology.org/data_1460 format: - term: PDB uri: http://edamontology.org/format_1476 homepage: http://inpsmd.biocomp.unibo.it homepage_status: 0 language: [] lastUpdate: '2024-03-11T16:56:00.844792Z' license: null link: [] maturity: Mature name: INPS-MD operatingSystem: - Linux - Windows - Mac otherID: [] owner: ELIXIR-ITA-BOLOGNA publication: - doi: 10.1093/bioinformatics/btv291 metadata: abstract: 'Motivation: A tool for reliably predicting the impact of variations on protein stability is extremely important for both protein engineering and for understanding the effects of Mendelian and somatic mutations in the genome. Next Generation Sequencing studies are constantly increasing the number of protein sequences. Given the huge disproportion between protein sequences and structures, there is a need for tools suited to annotate the effect of mutations starting from protein sequence without relying on the structure. Here, we describe INPS, a novel approach for annotating the effect of non-synonymous mutations on the protein stability from its sequence. INPS is based on SVM regression and it is trained to predict the thermodynamic free energy change upon single-point variations in protein sequences. Results: We show that INPS performs similarly to the state-of-the-art methods based on protein structure when tested in cross-validation on a non-redundant dataset. INPS performs very well also on a newly generated dataset consisting of a number of variations occurring in the tumor suppressor protein p53. Our results suggest that INPS is a tool suited for computing the effect of non-synonymous polymorphisms on protein stability when the protein structure is not available. We also show that INPS predictions are complementary to those of the state-of-the-art, structure-based method mCSM. When the two methods are combined, the overall prediction on the p53 set scores significantly higher than those of the single methods.' authors: - name: Fariselli P. - name: Martelli P.L. - name: Savojardo C. - name: Casadio R. citationCount: 94 date: '2015-02-06T00:00:00Z' journal: Bioinformatics title: 'INPS: Predicting the impact of non-synonymous variations on protein stability from sequence' note: null pmcid: null pmid: '25957347' type: - Primary version: null - doi: 10.1093/bioinformatics/btw192 metadata: abstract: 'Motivation: Protein function depends on its structural stability. The effects of single point variations on protein stability can elucidate the molecular mechanisms of human diseases and help in developing new drugs. Recently, we introduced INPS, a method suited to predict the effect of variations on protein stability from protein sequence and whose performance is competitive with the available state-of-the-art tools. Results: In this article, we describe INPS-MD (Impact of Non synonymous variations on Protein Stability-Multi-Dimension), a web server for the prediction of protein stability changes upon single point variation from protein sequence and/or structure. Here, we complement INPS with a new predictor (INPS3D) that exploits features derived from protein 3D structure. INPS3D scores with Pearson''s correlation to experimental ΔΔG values of 0.58 in cross validation and of 0.72 on a blind test set. The sequence-based INPS scores slightly lower than the structure-based INPS3D and both on the same blind test sets well compare with the state-of-the-art methods.' authors: - name: Savojardo C. - name: Fariselli P. - name: Martelli P.L. - name: Casadio R. citationCount: 147 date: '2016-08-15T00:00:00Z' journal: Bioinformatics title: 'INPS-MD: A web server to predict stability of protein variants from sequence and structure' note: null pmcid: null pmid: '27153629' type: - Primary version: null relation: [] toolType: - Web application topic: - term: Protein folding, stability and design uri: http://edamontology.org/topic_0130 - term: Genetic variation uri: http://edamontology.org/topic_0199 - term: Rare diseases uri: http://edamontology.org/topic_3325 validated: 1 version: - '2.0' - accessibility: Open access additionDate: '2015-01-22T11:31:41Z' biotoolsCURIE: biotools:snps_and_go biotoolsID: snps_and_go collectionID: - RD-connect - Rare Disease - Bologna Biocomputing Group community: null confidence_flag: tool cost: Free of charge credit: - email: null fundrefid: null gridid: null name: ELIXIR-ITA-BOLOGNA note: null orcidid: null rorid: null typeEntity: Institute typeRole: - Provider url: null - email: rita.casadio@unibo.it fundrefid: null gridid: null name: Rita Casadio note: null orcidid: null rorid: null typeEntity: Person typeRole: - Primary contact url: null - email: pierluigi.martelli@unibo.it fundrefid: null gridid: null name: Pier Luigi Martelli note: null orcidid: https://orcid.org/0000-0002-0274-5669 rorid: null typeEntity: Person typeRole: - Primary contact url: null description: A server for the prediction of single point protein mutations likely to be involved in the insurgence of diseases in humans.s. documentation: - note: null type: - General url: http://snps-and-go.biocomp.unibo.it/snps-and-go/help2.htm download: [] editPermission: authors: - ELIXIR-EE type: group elixirCommunity: - Rare Diseases elixirNode: - Italy elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: - data: term: UniProt accession uri: http://edamontology.org/data_3021 format: - term: Textual format uri: http://edamontology.org/format_2330 note: Prediction operation: - term: Data retrieval uri: http://edamontology.org/operation_2422 - term: Protein function analysis uri: http://edamontology.org/operation_2414 - term: Variant classification uri: http://edamontology.org/operation_3225 output: - data: term: Protein report uri: http://edamontology.org/data_0896 format: - term: Textual format uri: http://edamontology.org/format_2330 homepage: http://snps-and-go.biocomp.unibo.it/snps-and-go/index.html homepage_status: 0 language: [] lastUpdate: '2024-03-11T16:55:42.141343Z' license: null link: [] maturity: Mature name: SNPs and GO operatingSystem: - Linux - Windows - Mac otherID: [] owner: ELIXIR-ITA-BOLOGNA publication: - doi: 10.1002/humu.21047 metadata: abstract: Single nucleotide polymorphisms (SNPs) are the simplest and most frequent form of human DNA variation, also valuable as genetic markers of disease susceptibility. The most investigated SNPs are missense mutations resulting in residue substitutions in the protein. Here we propose SNPs&GO, an accurate method that, starting from a protein sequence, can predict whether a mutation is disease related or not by exploiting the protein functional annotation. The scoring efficiency of SNPs&GO is as high as 82%, with a Matthews correlation coefficient equal to 0.63 over a wide set of annotated nonsynonymous mutations in proteins, including 16,330 disease-related and 17,432 neutral polymorphisms. SNPs&GO collects in unique framework information derived from protein sequence, evolutionary information, and function as encoded in the Gene Ontology terms, and outperforms other available predictive methods. © 2009 Wiley-Liss, Inc. authors: - name: Calabrese R. - name: Capriotti E. - name: Fariselli P. - name: Martelli P.L. - name: Casadio R. citationCount: 486 date: '2009-08-01T00:00:00Z' journal: Human Mutation title: Functional annotations improve the predictive score of human disease-related mutations in proteins note: null pmcid: null pmid: null type: - Primary version: null relation: [] toolType: - Web application topic: - term: Genetic variation uri: http://edamontology.org/topic_0199 - term: Protein sites, features and motifs uri: http://edamontology.org/topic_3510 - term: Data mining uri: http://edamontology.org/topic_3473 - term: Rare diseases uri: http://edamontology.org/topic_3325 validated: 1 version: - '1.0' - accessibility: Open access additionDate: '2021-01-20T10:58:38Z' biotoolsCURIE: biotools:phenpath biotoolsID: phenpath collectionID: - Rare Disease - Bologna Biocomputing Group community: null confidence_flag: tool cost: Free of charge credit: - email: pierluigi.martelli@unibo.it fundrefid: null gridid: null name: Pier Luigi Martelli note: null orcidid: null rorid: null typeEntity: Person typeRole: - Primary contact url: null - email: giulia.babbi@unibo.it fundrefid: null gridid: null name: Giulia Babbi note: null orcidid: null rorid: null typeEntity: Person typeRole: - Developer - Primary contact url: null - email: null fundrefid: null gridid: null name: ELIXIR-ITA-BOLOGNA note: null orcidid: null rorid: null typeEntity: Institute typeRole: - Provider url: null description: 'A tool for characterizing biological functions underlying different phenotypes. a web server for associating phenotypes with molecular functional annotations. PhenPath includes a database and a tool:. ''' documentation: - note: null type: - User manual url: http://phenpath.biocomp.unibo.it/phenpath/help_page.html download: [] editPermission: authors: - ELIXIR-ITA-BOLOGNA type: group elixirCommunity: [] elixirNode: - Italy elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: - data: term: Disease ID uri: http://edamontology.org/data_1150 format: [] - data: term: Disease name uri: http://edamontology.org/data_3668 format: [] - data: term: Phenotype name uri: http://edamontology.org/data_3275 format: [] note: null operation: - term: Data retrieval uri: http://edamontology.org/operation_2422 - term: Enrichment analysis uri: http://edamontology.org/operation_3501 - term: Gene functional annotation uri: http://edamontology.org/operation_3672 output: - data: term: Disease report uri: http://edamontology.org/data_1622 format: [] homepage: http://phenpath.biocomp.unibo.it homepage_status: 0 language: [] lastUpdate: '2024-03-11T16:45:53.823541Z' license: CC-BY-NC-4.0 link: [] maturity: Mature name: PhenPath operatingSystem: - Linux - Mac - Windows otherID: [] owner: ELIXIR-ITA-BOLOGNA publication: - doi: 10.1186/S12864-019-5868-X metadata: abstract: 'Background: Many diseases are associated with complex patterns of symptoms and phenotypic manifestations. Parsimonious explanations aim at reconciling the multiplicity of phenotypic traits with the perturbation of one or few biological functions. For this, it is necessary to characterize human phenotypes at the molecular and functional levels, by exploiting gene annotations and known relations among genes, diseases and phenotypes. This characterization makes it possible to implement tools for retrieving functions shared among phenotypes, co-occurring in the same patient and facilitating the formulation of hypotheses about the molecular causes of the disease. Results: We introduce PhenPath, a new resource consisting of two parts: PhenPathDB and PhenPathTOOL. The former is a database collecting the human genes associated with the phenotypes described in Human Phenotype Ontology (HPO) and OMIM Clinical Synopses. Phenotypes are then associated with biological functions and pathways by means of NET-GE, a network-based method for functional enrichment of sets of genes. The present version considers only phenotypes related to diseases. PhenPathDB collects information for 18 OMIM Clinical synopses and 7137 HPO phenotypes, related to 4292 diseases and 3446 genes. Enrichment of Gene Ontology annotations endows some 87.7, 86.9 and 73.6% of HPO phenotypes with Biological Process, Molecular Function and Cellular Component terms, respectively. Furthermore, 58.8 and 77.8% of HPO phenotypes are also enriched for KEGG and Reactome pathways, respectively. Based on PhenPathDB, PhenPathTOOL analyzes user-defined sets of phenotypes retrieving diseases, genes and functional terms which they share. This information can provide clues for interpreting the co-occurrence of phenotypes in a patient. Conclusions: The resource allows finding molecular features useful to investigate diseases characterized by multiple phenotypes, and by this, it can help researchers and physicians in identifying molecular mechanisms and biological functions underlying the concomitant manifestation of phenotypes. The resource is freely available at http://phenpath.biocomp.unibo.it.' authors: - name: Babbi G. - name: Martelli P.L. - name: Casadio R. citationCount: 8 date: '2019-07-16T00:00:00Z' journal: BMC Genomics title: 'PhenPath: A tool for characterizing biological functions underlying different phenotypes' note: null pmcid: PMC6631446 pmid: '31307376' type: [] version: null relation: [] toolType: - Database portal topic: - term: Genotype and phenotype uri: http://edamontology.org/topic_0625 - term: Molecular interactions, pathways and networks uri: http://edamontology.org/topic_0602 - term: Pathology uri: http://edamontology.org/topic_0634 - term: Public health and epidemiology uri: http://edamontology.org/topic_3305 - term: Rare diseases uri: http://edamontology.org/topic_3325 validated: 0 version: [] - accessibility: Open access additionDate: '2017-03-01T16:16:45Z' biotoolsCURIE: biotools:ws_snps_and_go biotoolsID: ws_snps_and_go collectionID: - Rare Disease community: null confidence_flag: null cost: Free of charge credit: - email: null fundrefid: null gridid: null name: ELIXIR-ITA-BOLOGNA note: null orcidid: null rorid: null typeEntity: Institute typeRole: - Provider url: http://www.biocomp.unibo.it - email: emidio.capriotti@gmail.com fundrefid: null gridid: null name: Emidio Capriotti note: null orcidid: http://orcid.org/0000-0002-2323-0963 rorid: null typeEntity: Person typeRole: - Developer - Primary contact url: null - email: casadio@biocomp.unibo.it fundrefid: null gridid: null name: Rita Casadio note: null orcidid: null rorid: null typeEntity: Person typeRole: - Primary contact url: null description: A web server for predicting disease associated variations from protein sequence and structure. documentation: - note: null type: - General url: http://snps.biofold.org/snps-and-go/ download: - note: null type: Container file url: https://hub.docker.com/r/biofold/snps-and-go version: '2.0' editPermission: authors: - ELIXIR-EE - ELIXIR-ITA-BOLOGNA - emidio type: group elixirCommunity: - Rare Diseases elixirNode: - Italy elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: - data: term: PDB ID uri: http://edamontology.org/data_1127 format: - term: Textual format uri: http://edamontology.org/format_2330 - data: term: Protein chain uri: http://edamontology.org/data_1467 format: - term: Textual format uri: http://edamontology.org/format_2330 - data: term: GO concept ID uri: http://edamontology.org/data_1176 format: - term: Textual format uri: http://edamontology.org/format_2330 - data: term: Mutation ID uri: http://edamontology.org/data_2209 format: - term: Textual format uri: http://edamontology.org/format_2330 note: SNPs&GO 3D operation: - term: Variant classification uri: http://edamontology.org/operation_3225 output: - data: term: Disease report uri: http://edamontology.org/data_1622 format: - term: HTML uri: http://edamontology.org/format_2331 homepage: http://snps.biofold.org/snps-and-go homepage_status: 0 language: [] lastUpdate: '2024-03-07T13:23:43.848115Z' license: null link: [] maturity: Mature name: WS-SNPs-and-GO operatingSystem: - Linux - Windows - Mac otherID: [] owner: ELIXIR-ITA-BOLOGNA publication: - doi: 10.1186/1471-2105-12-S4-S3 metadata: abstract: 'Background: Single Nucleotide Polymorphisms (SNPs) are an important source of human genome variability. Non-synonymous SNPs occurring in coding regions result in single amino acid polymorphisms (SAPs) that may affect protein function and lead to pathology. Several methods attempt to estimate the impact of SAPs using different sources of information. Although sequence-based predictors have shown good performance, the quality of these predictions can be further improved by introducing new features derived from three-dimensional protein structures.Results: In this paper, we present a structure-based machine learning approach for predicting disease-related SAPs. We have trained a Support Vector Machine (SVM) on a set of 3,342 disease-related mutations and 1,644 neutral polymorphisms from 784 protein chains. We use SVM input features derived from the protein''s sequence, structure, and function. After dataset balancing, the structure-based method (SVM-3D) reaches an overall accuracy of 85%, a correlation coefficient of 0.70, and an area under the receiving operating characteristic curve (AUC) of 0.92. When compared with a similar sequence-based predictor, SVM-3D results in an increase of the overall accuracy and AUC by 3%, and correlation coefficient by 0.06. The robustness of this improvement has been tested on different datasets and in all the cases SVM-3D performs better than previously developed methods even when compared with PolyPhen2, which explicitly considers in input protein structure information.Conclusion: This work demonstrates that structural information can increase the accuracy of disease-related SAPs identification. Our results also quantify the magnitude of improvement on a large dataset. This improvement is in agreement with previously observed results, where structure information enhanced the prediction of protein stability changes upon mutation. Although the structural information contained in the Protein Data Bank is limiting the application and the performance of our structure-based method, we expect that SVM-3D will result in higher accuracy when more structural date become available. © 2011 Capriotti; licensee BioMed Central Ltd.' authors: - name: Capriotti E. - name: Altman R.B. citationCount: 97 date: '2011-07-05T00:00:00Z' journal: BMC Bioinformatics title: Improving the prediction of disease-related variants using protein three-dimensional structure note: null pmcid: PMC3194195 pmid: '21992054' type: - Method version: null - doi: 10.1002/humu.21047 metadata: abstract: Single nucleotide polymorphisms (SNPs) are the simplest and most frequent form of human DNA variation, also valuable as genetic markers of disease susceptibility. The most investigated SNPs are missense mutations resulting in residue substitutions in the protein. Here we propose SNPs&GO, an accurate method that, starting from a protein sequence, can predict whether a mutation is disease related or not by exploiting the protein functional annotation. The scoring efficiency of SNPs&GO is as high as 82%, with a Matthews correlation coefficient equal to 0.63 over a wide set of annotated nonsynonymous mutations in proteins, including 16,330 disease-related and 17,432 neutral polymorphisms. SNPs&GO collects in unique framework information derived from protein sequence, evolutionary information, and function as encoded in the Gene Ontology terms, and outperforms other available predictive methods. © 2009 Wiley-Liss, Inc. authors: - name: Calabrese R. - name: Capriotti E. - name: Fariselli P. - name: Martelli P.L. - name: Casadio R. citationCount: 486 date: '2009-08-01T00:00:00Z' journal: Human Mutation title: Functional annotations improve the predictive score of human disease-related mutations in proteins note: null pmcid: null pmid: '19514061' type: - Primary version: null relation: [] toolType: - Web application - Web service topic: - term: Protein properties uri: http://edamontology.org/topic_0123 - term: Pathology uri: http://edamontology.org/topic_0634 - term: Rare diseases uri: http://edamontology.org/topic_3325 validated: 1 version: - '2.0' - accessibility: Open access additionDate: '2015-01-22T11:45:55Z' biotoolsCURIE: biotools:signor biotoolsID: signor collectionID: - Rare Disease - COVID-19 - gpcr community: null confidence_flag: null cost: Free of charge credit: - email: livia.perfetto@fht.org fundrefid: null gridid: null name: Livia Perfetto note: null orcidid: null rorid: null typeEntity: Person typeRole: - Primary contact url: null - email: luana.licata@uniroma2.it fundrefid: null gridid: null name: Luana Licata note: null orcidid: https://orcid.org/0000-0001-5084-9000 rorid: null typeEntity: Person typeRole: - Contributor url: null - email: null fundrefid: null gridid: null name: Gianni Cesareni note: null orcidid: null rorid: null typeEntity: Person typeRole: - Contributor url: null - email: null fundrefid: null gridid: null name: Molecular Genetic Group, University of Rome "Tor Vergata", Rome, Italy note: null orcidid: null rorid: null typeEntity: Institute typeRole: - Provider url: null - email: null fundrefid: null gridid: null name: ELIXIR-ITA-TORVERGATA note: null orcidid: null rorid: null typeEntity: Institute typeRole: - Provider url: null - email: null fundrefid: null gridid: null name: Marta Iannuccelli note: null orcidid: null rorid: null typeEntity: Person typeRole: - Contributor url: null - email: null fundrefid: null gridid: null name: Alberto Calderone note: null orcidid: null rorid: null typeEntity: Person typeRole: - Developer url: null - email: null fundrefid: null gridid: null name: Prisca Lo Surdo note: null orcidid: null rorid: null typeEntity: Person typeRole: - Developer url: null - email: null fundrefid: null gridid: null name: Leonardo Briganti note: null orcidid: null rorid: null typeEntity: Person typeRole: - Developer url: null description: A tool collects manually-annotated logic relationships between molecules that participate in signal transduction. documentation: - note: null type: - General url: http://signor.uniroma2.it/user_guide.php download: - note: null type: API specification url: https://signor.uniroma2.it/downloads.php version: null editPermission: authors: - mbermudez1 type: group elixirCommunity: [] elixirNode: - Italy elixirPlatform: - Data elixir_badge: 0 function: - cmd: null input: [] note: Data curation and annotation operation: - term: Deposition uri: http://edamontology.org/operation_3431 output: [] - cmd: null input: - data: term: Text data uri: http://edamontology.org/data_2526 format: - term: PSI MI TAB (MITAB) uri: http://edamontology.org/format_3242 note: Pathway or network operation: - term: Pathway or network visualisation uri: http://edamontology.org/operation_3083 output: - data: term: Pathway or network uri: http://edamontology.org/data_2600 format: - term: Textual format uri: http://edamontology.org/format_2330 homepage: http://signor.uniroma2.it/ homepage_status: 0 language: [] lastUpdate: '2024-02-15T12:49:43.873004Z' license: CC-BY-SA-4.0 link: [] maturity: Mature name: SIGNOR operatingSystem: - Linux - Windows - Mac otherID: [] owner: ELIXIR-ITA-TORVERGATA publication: - doi: 10.1093/nar/gkz949 metadata: abstract: 'The SIGnaling Network Open Resource 2.0 (SIGNOR 2.0) is a public repository that stores signaling information as binary causal relationships between biological entities. The captured information is represented graphically as a signed directed graph. Each signaling relationship is associated to an effect (up/down-regulation) and to the mechanism (e.g. binding, phosphorylation, transcriptional activation, etc.) causing the up/down-regulation of the target entity. Since its first release, SIGNOR has undergone a significant content increase and the number of annotated causal interactions have almost doubled. SIGNOR 2.0 now stores almost 23 000 manually-annotated causal relationships between proteins and other biologically relevant entities: chemicals, phenotypes, complexes, etc. We describe here significant changes in curation policy and a new confidence score, which is assigned to each interaction. We have also improved the compliance to the FAIR data principles by providing (i) SIGNOR stable identifiers, (ii) programmatic access through REST APIs, (iii) bioschemas and (iv) downloadable data in standard-compliant formats, such as PSI-MI CausalTAB and GMT. The data are freely accessible and downloadable at https://signor.uniroma2.it/.' authors: - name: Licata L. - name: Lo Surdo P. - name: Iannuccelli M. - name: Palma A. - name: Micarelli E. - name: Perfetto L. - name: Peluso D. - name: Calderone A. - name: Castagnoli L. - name: Cesareni G. citationCount: 147 date: '2020-01-01T00:00:00Z' journal: Nucleic Acids Research title: 'SIGNOR 2.0, the SIGnaling Network Open Resource 2.0: 2019 update' note: null pmcid: null pmid: '31665520' type: - Primary version: null - doi: 10.1093/nar/gkv1048 metadata: abstract: Assembly of large biochemical networks can be achieved by confronting new cell-specific experimental data with an interaction subspace constrained by prior literature evidence. The SIGnaling Network Open Resource, SIGNOR (available on line at http://signor.uniroma2.it), was developed to support such a strategy by providing a scaffold of prior experimental evidence of causal relationships between biological entities. The core of SIGNOR is a collection of approximately 12 000 manuallyannotated causal relationships between over 2800 human proteins participating in signal transduction. Other entities annotated in SIGNOR are complexes, chemicals, phenotypes and stimuli. The information captured in SIGNOR can be represented as a signed directed graph illustrating the activation/inactivation relationships between signalling entities. Each entry is associated to the post-translational modifications that cause the activation/inactivation of the target proteins. More than 4900 modified residues causing a change in protein concentration or activity have been curated and linked to the modifying enzymes (about 351 human kinases and 94 phosphatases). Additional modifications such as ubiquitinations, sumoylations, acetylations and their effect on the modified target proteins are also annotated. This wealth of structured information can support experimental approaches based on multi-parametric analysis of cell systems after physiological or pathological perturbations and to assemble large logic models. authors: - name: Perfetto L. - name: Briganti L. - name: Calderone A. - name: Perpetuini A.C. - name: Iannuccelli M. - name: Langone F. - name: Licata L. - name: Marinkovic M. - name: Mattioni A. - name: Pavlidou T. - name: Peluso D. - name: Petrilli L.L. - name: Pirro S. - name: Posca D. - name: Santonico E. - name: Silvestri A. - name: Spada F. - name: Castagnoli L. - name: Cesareni G. citationCount: 172 date: '2016-01-01T00:00:00Z' journal: Nucleic Acids Research title: 'SIGNOR: A database of causal relationships between biological entities' note: null pmcid: null pmid: null type: - Other version: null - doi: 10.1002/cpbi.28 metadata: abstract: 'SIGNOR (http://signor.uniroma2.it), the SIGnaling Network Open Resource, is a database designed to store experimentally validated causal interactions, i.e., interactions where a source entity has a regulatory effect (up-regulation, down-regulation, etc.) on a second target entity. SIGNOR acts both as a source of signaling information and a support for data analysis, modeling, and prediction. A user-friendly interface features the ability to search entries for any given protein or group of proteins and to display their interactions graphically in a network view. At the time of writing, SIGNOR stores approximately 16,000 manually curated interactions connecting more than 4,000 biological entities (proteins, chemicals, protein complexes, etc.) that play a role in signal transduction. SIGNOR also offers a collection of 37 signaling pathways. SIGNOR can be queried by three search tools: “single-entity” search, “multiple-entity” search, and “pathway” search. This manuscript describes two basic protocols detailing how to navigate and search the SIGNOR database and how to download the annotated dataset for local use. Finally, the support protocol reviews the utilities of the graphic visualizer.' authors: - name: Surdo P.L. - name: Calderone A. - name: Cesareni G. - name: Perfetto L. citationCount: 11 date: '2017-06-01T00:00:00Z' journal: Current Protocols in Bioinformatics title: 'SIGNOR: A database of causal relationships between biological entities-a short guide to searching and browsing' note: null pmcid: null pmid: '28654729' type: - Method version: null relation: [] toolType: - Database portal topic: - term: Molecular interactions, pathways and networks uri: http://edamontology.org/topic_0602 - term: Rare diseases uri: http://edamontology.org/topic_3325 validated: 1 version: - '2.0' - accessibility: Open access additionDate: '2017-09-26T07:45:59Z' biotoolsCURIE: biotools:rediportal biotoolsID: rediportal collectionID: - Rare Disease community: null confidence_flag: null cost: Free of charge credit: - email: null fundrefid: null gridid: null name: null note: null orcidid: null rorid: null typeEntity: Person typeRole: - Primary contact url: http://srv00.recas.ba.infn.it/atlas/contact.html description: Database of A-to-I (deamination of adenosines to inosines) events that enables to search RNA editing sites by genomic region, gene name and other relevant features as the tissue of origin. documentation: - note: null type: - User manual url: http://srv00.recas.ba.infn.it/atlas/help.html download: - note: null type: Downloads page url: http://srv00.recas.ba.infn.it/atlas/download.html version: null editPermission: authors: - ELIXIR-ITA-BARI type: group elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: [] note: null operation: - term: Structure editing uri: http://edamontology.org/operation_3080 - term: Editing uri: http://edamontology.org/operation_3096 - term: Genotyping uri: http://edamontology.org/operation_3196 - term: Gene expression profiling uri: http://edamontology.org/operation_0314 - term: Query and retrieval uri: http://edamontology.org/operation_0224 output: [] homepage: http://srv00.recas.ba.infn.it/atlas/ homepage_status: 0 language: - Java - SQL - Python lastUpdate: '2024-02-09T14:51:17.618389Z' license: null link: [] maturity: Mature name: REDIportal operatingSystem: - Linux - Windows - Mac otherID: [] owner: ELIXIR-EE publication: - doi: 10.1093/nar/gkw767 metadata: abstract: RNA editing by A-to-I deamination is the prominent co-/post-transcriptional modification in humans. It is carried out by ADAR enzymes and contributes to both transcriptomic and proteomic expansion. RNA editing has pivotal cellular effects and its deregulation has been linked to a variety of human disorders including neurological and neurodegenerative diseases and cancer. Despite its biological relevance, many physiological and functional aspects of RNA editing are yet elusive. Here, we present REDIportal, available online at http://srv00.recas.ba.infn.it/atlas/, the largest and comprehensive collection of RNA editing in humans including more than 4.5 millions of A-to-I events detected in 55 body sites from thousands of RNAseq experiments. REDIportal embeds RADAR database and represents the first editing resource designed to answer functional questions, enabling the inspection and browsing of editing levels in a variety of human samples, tissues and body sites. In contrast with previous RNA editing databases, REDIportal comprises its own browser (JBrowse) that allows users to explore A-to-I changes in their genomic context, empathizing repetitive elements in which RNA editing is prominent. authors: - name: Picardi E. - name: D'Erchia A.M. - name: Giudice C.L. - name: Pesole G. citationCount: 201 date: '2017-01-01T00:00:00Z' journal: Nucleic Acids Research title: 'REDIportal: A comprehensive database of A-to-I RNA editing events in humans' note: null pmcid: PMC5210607 pmid: '27587585' type: - Primary version: null - doi: 10.1093/nar/gkaa916 metadata: abstract: RNA editing is a relevant epitranscriptome phenomenon able to increase the transcriptome and proteome diversity of eukaryotic organisms. ADAR mediated RNA editing is widespread in humans in which millions of A-to-I changes modify thousands of primary transcripts. RNA editing has pivotal roles in the regulation of gene expression or modulation of the innate immune response or functioning of several neurotransmitter receptors. Massive transcriptome sequencing has fostered the research in this field. Nonetheless, different aspects of the RNA editing biology are still unknown and need to be elucidated. To support the study of A-to-I RNA editing we have updated our REDIportal catalogue raising its content to about 16 millions of events detected in 9642 human RNAseq samples from the GTEx project by using a dedicated pipeline based on the HPC version of the REDItools software. REDIportal now allows searches at sample level, provides overviews of RNA editing profiles per each RNAseq experiment, implements a Gene View module to look at individual events in their genic context and hosts the CLAIRE database. Starting from this novel version, REDIportal will start collecting non-human RNA editing changes for comparative genomics investigations. The database is freely available at http://srv00.recas.ba.infn.it/atlas/index.html. authors: - name: Mansi L. - name: Tangaro M.A. - name: Lo Giudice C. - name: Flati T. - name: Kopel E. - name: Schaffer A.A. - name: Castrignano T. - name: Chillemi G. - name: Pesole G. - name: Picardi E. citationCount: 62 date: '2021-01-08T00:00:00Z' journal: Nucleic Acids Research title: 'REDIportal: Millions of novel A-to-I RNA editing events from thousands of RNAseq experiments' note: null pmcid: PMC7778987 pmid: '33104797' type: - Primary version: null - doi: 10.1038/s41596-019-0279-7 metadata: abstract: RNA editing is a widespread post-transcriptional mechanism able to modify transcripts through insertions/deletions or base substitutions. It is prominent in mammals, in which millions of adenosines are deaminated to inosines by members of the ADAR family of enzymes. A-to-I RNA editing has a plethora of biological functions, but its detection in large-scale transcriptome datasets is still an unsolved computational task. To this aim, we developed REDItools, the first software package devoted to the RNA editing profiling in RNA-sequencing (RNAseq) data. It has been successfully used in human transcriptomes, proving the tissue and cell type specificity of RNA editing as well as its pervasive nature. Outcomes from large-scale REDItools analyses on human RNAseq data have been collected in our specialized REDIportal database, containing more than 4.5 million events. Here we describe in detail two bioinformatic procedures based on our computational resources, REDItools and REDIportal. In the first procedure, we outline a workflow to detect RNA editing in the human cell line NA12878, for which transcriptome and whole genome data are available. In the second procedure, we show how to identify dysregulated editing at specific recoding sites in post-mortem brain samples of Huntington disease donors. On a 64-bit computer running Linux with ≥32 GB of random-access memory (RAM), both procedures should take ~76 h, using 4 to 24 cores. Our protocols have been designed to investigate RNA editing in different organisms with available transcriptomic and/or genomic reads. Scripts to complete both procedures and a docker image are available at https://github.com/BioinfoUNIBA/REDItools. authors: - name: Lo Giudice C. - name: Tangaro M.A. - name: Pesole G. - name: Picardi E. citationCount: 69 date: '2020-03-01T00:00:00Z' journal: Nature Protocols title: Investigating RNA editing in deep transcriptome datasets with REDItools and REDIportal note: null pmcid: null pmid: '31996844' type: - Usage version: null - doi: 10.1007/978-1-0716-1307-8_25 metadata: abstract: A-to-I RNA editing in humans plays a relevant role since it can influence gene expression and increase proteome diversity. In addition, its deregulation has been linked to a variety of human diseases, including neurological disorders and cancer. In the last decade, massive transcriptome sequencing through the RNAseq technology has dramatically improved the investigation of RNA editing at single nucleotide resolution. Nowadays, different bioinformatics resources to discover and/or collect A-to-I events have been released. Hereafter, we initially provide an overview of the state-of-the-art RNA editing databases and, then, we focus on REDIportal, the largest collection of A-to-I events with more than 4.5 million sites from 2660 humans GTEx samples. authors: - name: Giudice C.L. - name: Mansi L. - name: Pesole G. - name: Picardi E. citationCount: 1 date: '2021-01-01T00:00:00Z' journal: Methods in Molecular Biology title: Databases for RNA Editing Collections note: null pmcid: null pmid: '33835458' type: - Usage version: null relation: [] toolType: - Web application topic: - term: RNA-Seq uri: http://edamontology.org/topic_3170 - term: Sequencing uri: http://edamontology.org/topic_3168 - term: RNA uri: http://edamontology.org/topic_0099 - term: Transcriptomics uri: http://edamontology.org/topic_3308 - term: Gene transcripts uri: http://edamontology.org/topic_3512 - term: Rare diseases uri: http://edamontology.org/topic_3325 validated: 1 version: [] - accessibility: null additionDate: '2024-02-04T23:51:01.271603Z' biotoolsCURIE: biotools:bravo biotoolsID: bravo collectionID: - Rare Disease community: null confidence_flag: null cost: null credit: [] description: BRowse All Variants Online - Variant Visualization Tool documentation: [] download: - note: null type: Downloads page url: https://github.com/statgen/bravo version: null editPermission: authors: [] type: public elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: [] note: null operation: - term: Genome visualisation uri: http://edamontology.org/operation_3208 output: [] homepage: https://bravo.sph.umich.edu/ homepage_status: 0 language: [] lastUpdate: '2024-02-05T00:23:44.655238Z' license: null link: [] maturity: null name: Bravo operatingSystem: - Linux otherID: [] owner: emidio publication: [] relation: [] toolType: - Web application topic: - term: Genetic variation uri: http://edamontology.org/topic_0199 - term: DNA mutation uri: http://edamontology.org/topic_2533 validated: 0 version: [] - accessibility: Open access additionDate: '2017-03-24T11:31:31Z' biotoolsCURIE: biotools:ebi_tools biotoolsID: ebi_tools collectionID: - EBI Tools - Job Dispatcher Tools - BioExcel - Rare Disease - COVID-19 community: null confidence_flag: null cost: Free of charge credit: - email: null fundrefid: null gridid: null name: EMBL - EBI note: null orcidid: null rorid: null typeEntity: Institute typeRole: - Provider url: null - email: null fundrefid: null gridid: null name: Job Dispatcher note: null orcidid: null rorid: null typeEntity: Project typeRole: - Primary contact url: http://www.ebi.ac.uk/jdispatcher/ description: EBI Tools is a project that aims to provide programmatic access to the various databases and retrieval and analysis services that the European Bioinformatics Institute (EBI) provides through Simple Object Access Protocol (SOAP) and other related web service technologies. Example tools include those to compute sequence similarity searches, pairwise/multiple sequence alignment and protein functional analysis. documentation: - note: null type: - Terms of use url: http://www.ebi.ac.uk/about/terms-of-use - note: null type: - General url: http://www.ebi.ac.uk/Tools/webservices/ download: [] editPermission: authors: - biomadeira - nandana type: group elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: [] note: null operation: - term: Sequence similarity search uri: http://edamontology.org/operation_0346 - term: Data retrieval uri: http://edamontology.org/operation_2422 - term: Protein function analysis uri: http://edamontology.org/operation_2414 - term: Query and retrieval uri: http://edamontology.org/operation_0224 - term: Multiple sequence alignment uri: http://edamontology.org/operation_0492 output: [] homepage: http://www.ebi.ac.uk/Tools/webservices/ homepage_status: 0 language: - Java - Perl - Python lastUpdate: '2024-01-12T16:26:19.081861Z' license: null link: - note: null type: - Helpdesk url: http://www.ebi.ac.uk/support/ maturity: Mature name: EBI Tools operatingSystem: - Linux - Windows - Mac otherID: [] owner: jdispatcher publication: - doi: 10.1093/nar/gkac240 metadata: abstract: The EMBL-EBI search and sequence analysis tools frameworks provide integrated access to EMBL-EBI's data resources and core bioinformatics analytical tools. EBI Search (https://www.ebi.ac.uk/ebisearch) provides a full-text search engine across nearly 5 billion entries, while the Job Dispatcher tools framework (https://www.ebi.ac.uk/services) enables the scientific community to perform a diverse range of sequence analysis using popular bioinformatics applications. Both allow users to interact through user-friendly web applications, as well as via RESTful and SOAP-based APIs. Here, we describe recent improvements to these services and updates made to accommodate the increasing data requirements during the COVID-19 pandemic. authors: - name: Madeira F. - name: Pearce M. - name: Tivey A.R.N. - name: Basutkar P. - name: Lee J. - name: Edbali O. - name: Madhusoodanan N. - name: Kolesnikov A. - name: Lopez R. citationCount: 651 date: '2022-07-05T00:00:00Z' journal: Nucleic Acids Research title: Search and sequence analysis tools services from EMBL-EBI in 2022 note: null pmcid: null pmid: null type: - Primary version: null - doi: 10.1093/nar/gkp302 metadata: abstract: The European Bioinformatics Institute (EMBL-EBI) has been providing access to mainstream databases and tools in bioinformatics since 1997. In addition to the traditional web form based interfaces, APIs exist for core data resources such as EMBL-Bank, Ensembl, UniProt, InterPro, PDB and ArrayExpress. These APIs are based on Web Services (SOAP/REST) interfaces that allow users to systematically access databases and analytical tools. From the user's point of view, these Web Services provide the same functionality as the browser-based forms. However, using the APIs frees the user from web page constraints and are ideal for the analysis of large batches of data, performing text-mining tasks and the casual or systematic evaluation of mathematical models in regulatory networks. Furthermore, these services are widespread and easy to use; require no prior knowledge of the technology and no more than basic experience in programming. In the following we wish to inform of new and updated services as well as briefly describe planned developments to be made available during the course of 2009-2010. authors: - name: Mcwilliam H. - name: Valentin F. - name: Goujon M. - name: Li W. - name: Narayanasamy M. - name: Martin J. - name: Miyar T. - name: Lopez R. citationCount: 62 date: '2009-08-04T00:00:00Z' journal: Nucleic Acids Research title: Web services at the European Bioinformatics Institute-2009 note: null pmcid: PMC2703973 pmid: '19435877' type: - Primary version: null - doi: 10.1093/nar/gkh405 metadata: abstract: 'The mission of the European Bioinformatics Institute (EBI), an outstation of the European Molecular Biology Laboratory (EMBL) in Heidelberg, is to ensure that the growing body of information from molecular biology and genome research is placed in the public domain and is accessible freely to all parts of the scientific community in ways that promote scientific progress. To fulfil this mission, the EBI provides a wide variety of free, publicly available bioinformatics services. These can be divided into data submissions processing; access to query, analysis and retrieval systems and tools; ftp downloads of software and databases; training and education and user support. All of these services are available at the EBI website: http://www.ebi.ac.uk/services. This paper provides a detailed introduction to the interactive analysis systems that are available from the EBI and a brief introduction to other, related services. © Oxford University Press 2004; all rights reserved.' authors: - name: Harte N. - name: Silventoinen V. - name: Quevillon E. - name: Robinson S. - name: Kallio K. - name: Fustero X. - name: Patel P. - name: Jokinen P. - name: Lopez R. citationCount: 23 date: '2004-07-01T00:00:00Z' journal: Nucleic Acids Research title: Public web-based services from the European Bioinformatics Institute note: null pmcid: PMC441543 pmid: '15215339' type: - Primary version: null - doi: 10.1093/nar/gkm291 metadata: null note: null pmcid: PMC1933145 pmid: '17576686' type: - Primary version: null - doi: 10.1093/nar/gkt376 metadata: null note: null pmcid: PMC3692137 pmid: '23671338' type: - Primary version: null - doi: 10.1093/nar/gkv1352 metadata: null note: null pmcid: null pmid: null type: - Primary version: null - doi: 10.1093/nar/gki491 metadata: null note: null pmcid: null pmid: null type: - Other version: null relation: [] toolType: - Web API - Web application - Web service topic: - term: Proteins uri: http://edamontology.org/topic_0078 - term: Bioinformatics uri: http://edamontology.org/topic_0091 - term: Function analysis uri: http://edamontology.org/topic_1775 - term: Molecular interactions, pathways and networks uri: http://edamontology.org/topic_0602 - term: Sequence analysis uri: http://edamontology.org/topic_0080 - term: Rare diseases uri: http://edamontology.org/topic_3325 validated: 1 version: [] - accessibility: Open access additionDate: '2022-11-04T11:11:36.831993Z' biotoolsCURIE: biotools:jdispatcher biotoolsID: jdispatcher collectionID: - EBI Tools - Job Dispatcher Tools - BioExcel - Rare Disease - COVID-19 community: null confidence_flag: null cost: Free of charge credit: - email: null fundrefid: null gridid: null name: EMBL - EBI note: null orcidid: null rorid: null typeEntity: Institute typeRole: - Provider url: null - email: null fundrefid: null gridid: null name: Job Dispatcher note: null orcidid: null rorid: null typeEntity: Project typeRole: - Primary contact url: http://www.ebi.ac.uk/jdispatcher/ description: EBI Tools is a project that aims to provide programmatic access to the various databases and retrieval and analysis services that the European Bioinformatics Institute (EBI) provides through Simple Object Access Protocol (SOAP) and other related web service technologies. Example tools include those to compute sequence similarity searches, pairwise/multiple sequence alignment and protein functional analysis. documentation: - note: null type: - Terms of use url: http://www.ebi.ac.uk/about/terms-of-use - note: null type: - General url: https://www.ebi.ac.uk/jdispatcher/help download: [] editPermission: authors: - biomadeira - nandana type: group elixirCommunity: [] elixirNode: [] elixirPlatform: [] elixir_badge: 0 function: - cmd: null input: [] note: null operation: - term: Sequence similarity search uri: http://edamontology.org/operation_0346 - term: Data retrieval uri: http://edamontology.org/operation_2422 - term: Protein function analysis uri: http://edamontology.org/operation_2414 - term: Query and retrieval uri: http://edamontology.org/operation_0224 - term: Multiple sequence alignment uri: http://edamontology.org/operation_0492 output: [] homepage: http://www.ebi.ac.uk/jdispatcher/ homepage_status: 0 language: - Java - Perl - Python lastUpdate: '2024-01-12T15:31:09.037111Z' license: null link: - note: null type: - Helpdesk url: https://www.ebi.ac.uk/about/contact/support/job-dispatcher-services maturity: Mature name: Job Dispatcher operatingSystem: - Linux - Windows - Mac otherID: [] owner: jdispatcher publication: - doi: 10.1093/nar/gkac240 metadata: abstract: The EMBL-EBI search and sequence analysis tools frameworks provide integrated access to EMBL-EBI's data resources and core bioinformatics analytical tools. EBI Search (https://www.ebi.ac.uk/ebisearch) provides a full-text search engine across nearly 5 billion entries, while the Job Dispatcher tools framework (https://www.ebi.ac.uk/services) enables the scientific community to perform a diverse range of sequence analysis using popular bioinformatics applications. Both allow users to interact through user-friendly web applications, as well as via RESTful and SOAP-based APIs. Here, we describe recent improvements to these services and updates made to accommodate the increasing data requirements during the COVID-19 pandemic. authors: - name: Madeira F. - name: Pearce M. - name: Tivey A.R.N. - name: Basutkar P. - name: Lee J. - name: Edbali O. - name: Madhusoodanan N. - name: Kolesnikov A. - name: Lopez R. citationCount: 651 date: '2022-07-05T00:00:00Z' journal: Nucleic Acids Research title: Search and sequence analysis tools services from EMBL-EBI in 2022 note: null pmcid: null pmid: null type: - Primary version: null - doi: 10.1093/nar/gkz268 metadata: abstract: The EMBL-EBI provides free access to popular bioinformatics sequence analysis applications as well as to a full-featured text search engine with powerful cross-referencing and data retrieval capabilities. Access to these services is provided via user-friendly web interfaces and via established RESTful and SOAP Web Services APIs (https://www.ebi.ac.uk/seqdb/confluence/display/JDSAT/EMBL-EBI+Web+Services+APIs+-+Data+Retrieval). Both systems have been developed with the same core principles that allow them to integrate an ever-increasing volume of biological data, making them an integral part of many popular data resources provided at the EMBL-EBI. Here, we describe the latest improvements made to the frameworks which enhance the interconnectivity between public EMBL-EBI resources and ultimately enhance biological data discoverability, accessibility, interoperability and reusability. authors: - name: Madeira F. - name: Park Y.M. - name: Lee J. - name: Buso N. - name: Gur T. - name: Madhusoodanan N. - name: Basutkar P. - name: Tivey A.R.N. - name: Potter S.C. - name: Finn R.D. - name: Lopez R. citationCount: 2935 date: '2019-07-01T00:00:00Z' journal: Nucleic Acids Research title: The EMBL-EBI search and sequence analysis tools APIs in 2019 note: null pmcid: null pmid: null type: - Other version: null relation: [] toolType: - Web API - Web application - Web service topic: - term: Proteins uri: http://edamontology.org/topic_0078 - term: Bioinformatics uri: http://edamontology.org/topic_0091 - term: Function analysis uri: http://edamontology.org/topic_1775 - term: Molecular interactions, pathways and networks uri: http://edamontology.org/topic_0602 - term: Sequence analysis uri: http://edamontology.org/topic_0080 - term: Rare diseases uri: http://edamontology.org/topic_3325 validated: 0 version: [] next: ?page=2 previous: null