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https://www.maizegdb.org/effect/maize/", "biotoolsID": "paneffect", "biotoolsCURIE": "biotools:paneffect", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0331", "term": "Variant effect prediction" }, { "uri": "http://edamontology.org/operation_3225", "term": "Variant classification" }, { "uri": "http://edamontology.org/operation_0267", "term": "Protein secondary structure prediction" }, { "uri": "http://edamontology.org/operation_0303", "term": "Fold recognition" }, { "uri": "http://edamontology.org/operation_1812", "term": "Parsing" } ], "input": [], "output": [], "note": null, "cmd": null } ], "toolType": [ "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0625", "term": "Genotype and phenotype" }, { "uri": "http://edamontology.org/topic_0199", "term": "Genetic variation" }, { "uri": "http://edamontology.org/topic_0121", "term": "Proteomics" }, { "uri": "http://edamontology.org/topic_3120", "term": "Protein variants" }, { "uri": "http://edamontology.org/topic_3517", "term": "GWAS study" } ], "operatingSystem": [ "Mac", "Linux", "Windows" ], "language": [ "JavaScript", "Python" ], "license": "MIT", "collectionID": [], "maturity": null, "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/Maize-Genetics-and-Genomics-Database/PanEffect", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/bioinformatics/btae073", "pmid": "38337024", "pmcid": "PMC10881103", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "PanEffect: a pan-genome visualization tool for variant effects in maize", "abstract": "Understanding the effects of genetic variants is crucial for accurately predicting traits and functional outcomes. Recent approaches have utilized artificial intelligence and protein language models to score all possible missense variant effects at the proteome level for a single genome, but a reliable tool is needed to explore these effects at the pan-genome level. To address this gap, we introduce a new tool called PanEffect. We implemented PanEffect at MaizeGDB to enable a comprehensive examination of the potential effects of coding variants across 50 maize genomes. The tool allows users to visualize over 550 million possible amino acid substitutions in the B73 maize reference genome and to observe the effects of the 2.3 million natural variations in the maize pan-genome. Each variant effect score, calculated from the Evolutionary Scale Modeling (ESM) protein language model, shows the log-likelihood ratio difference between B73 and all variants in the pan-genome. These scores are shown using heatmaps spanning benign outcomes to potential functional consequences. In addition, PanEffect displays secondary structures and functional domains along with the variant effects, offering additional functional and structural context. Using PanEffect, researchers now have a platform to explore protein variants and identify genetic targets for crop enhancement.", "date": "2024-02-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Andorf C.M." }, { "name": "Haley O.C." }, { "name": "Hayford R.K." }, { "name": "Portwood J.L." }, { "name": "Harding S." }, { "name": "Sen S." }, { "name": "Cannon E.K." }, { "name": "Gardiner J.M." }, { "name": "Kim H.-S." }, { "name": "Woodhouse M.R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "Carson M Andorf", "email": "carson.andorf@usda.gov", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [], "note": null } ], "community": null, "owner": "Pub2Tools", "additionDate": "2024-03-18T15:24:22.036965Z", "lastUpdate": "2024-03-18T15:24:22.039569Z", "editPermission": { "type": "public", "authors": [] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Infernal", "description": "Infernal (\"INFERence of RNA ALignment\") is for searching DNA sequence databases for RNA structure and sequence similarities. It is an implementation of a special case of profile stochastic context-free grammars called covariance models (CMs). A CM is like a sequence profile, but it scores a combination of sequence consensus and RNA secondary structure consensus, so in many cases, it is more capable of identifying RNA homologs that conserve their secondary structure more than their primary sequence.", "homepage": "http://eddylab.org/infernal/", "biotoolsID": "infernal", "biotoolsCURIE": "biotools:infernal", "version": [], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0415", "term": "Nucleic acid feature detection" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1354", "term": "Sequence profile" }, "format": [ { "uri": "http://edamontology.org/format_2069", "term": "Sequence profile format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2080", "term": "Database search results" }, "format": [] } ], "note": null, "cmd": null } ], "toolType": [ "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_0160", "term": "Sequence sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0122", "term": "Structural genomics" } ], "operatingSystem": [], "language": [ "C" ], "license": "BSD-3-Clause", "collectionID": [], "maturity": null, "cost": null, "accessibility": null, "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://github.com/EddyRivasLab/infernal", "type": [ "Repository" ], "note": null } ], "download": [], "documentation": [], "publication": [ { "doi": "10.1093/bioinformatics/btt509", "pmid": "24008419", "pmcid": "PMC3810854", "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "Infernal 1.1: 100-fold faster RNA homology searches", "abstract": "Summary: Infernal builds probabilistic profiles of the sequence and secondary structure of an RNA family called covariance models (CMs) from structurally annotated multiple sequence alignments given as input. Infernal uses CMs to search for new family members in sequence databases and to create potentially large multiple sequence alignments. Version 1.1 of Infernal introduces a new filter pipeline for RNA homology search based on accelerated profile hidden Markov model (HMM) methods and HMM-banded CM alignment methods. This enables ∼100-fold acceleration over the previous version and ∼10 000-fold acceleration over exhaustive non-filtered CM searches. © The Author 2013. Published by Oxford University Press. All rights reserved.", "date": "2013-11-15T00:00:00Z", "citationCount": 1726, "authors": [ { "name": "Nawrocki E.P." }, { "name": "Eddy S.R." } ], "journal": "Bioinformatics" } } ], "credit": [], "community": null, "owner": "leipzig", "additionDate": "2021-02-16T16:35:35Z", "lastUpdate": "2024-03-15T10:10:42.236331Z", "editPermission": { "type": "group", "authors": [ "sergitobara", "alexcorm", "ELIXIR-CZ", "bebatut" ] }, "validated": 0, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "PredGPI", "description": "Prediction system for GPI-anchored proteins.", "homepage": "https://busca.biocomp.unibo.it/predgpi", "biotoolsID": "predgpi", "biotoolsCURIE": "biotools:predgpi", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3351", "term": "Molecular surface analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": "Prediction", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_3542", "term": "Protein secondary structure" }, { "uri": "http://edamontology.org/topic_0123", "term": "Protein properties" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "Bologna Biocomputing Group" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://gpcr.biocomp.unibo.it/predgpi", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1186/1471-2105-9-392", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "PredGPI: A GPI-anchor predictor", "abstract": "Background: Several eukaryotic proteins associated to the extracellular leaflet of the plasma membrane carry a Glycosylphosphatidylinositol (GPI) anchor, which is linked to the C-terminal residue after a proteolytic cleavage occurring at the so called ω-site. Computational methods were developed to discriminate proteins that undergo this post-translational modification starting from their aminoacidic sequences. However more accurate methods are needed for a reliable annotation of whole proteomes. Results: Here we present PredGPI, a prediction method that, by coupling a Hidden Markov Model (HMM) and a Support Vector Machine (SVM), is able to efficiently predict both the presence of the GPI-anchor and the position of the ω-site. PredGPI is trained on a non-redundant dataset of experimentally characterized GPI-anchored proteins whose annotation was carefully checked in the literature. Conclusion: PredGPI outperforms all the other previously described methods and is able to correctly replicate the results of previously published high-throughput experiments. PredGPI reaches a lower rate of false positive predictions with respect to other available methods and it is therefore a costless, rapid and accurate method for screening whole proteomes. © 2008 Pierleoni et al; licensee BioMed Central Ltd.", "date": "2008-09-23T00:00:00Z", "citationCount": 463, "authors": [ { "name": "Pierleoni A." }, { "name": "Martelli P." }, { "name": "Casadio R." } ], "journal": "BMC Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Andrea Pierleoni", "email": "andrea@biocomp.unibo.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Rita Casadio", "email": "casadio@biocomp.unibo.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Pier Luigi Martelli", "email": "pierluigi.martelli@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-0274-5669", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null } ], "community": null, "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2015-01-22T11:31:41Z", "lastUpdate": "2024-03-15T09:45:28.215746Z", "editPermission": { "type": "group", "authors": [ "Nimna" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "BaCelLo", "description": "Predictor for the subcellular localization of proteins in eukaryotes.", "homepage": "https://busca.biocomp.unibo.it/bacello", "biotoolsID": "bacello", "biotoolsCURIE": "biotools:bacello", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2489", "term": "Protein subcellular localisation prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_0849", "term": "Sequence record" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": "Prediction for the subcellular localization", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0140", "term": "Protein targeting and localisation" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" }, { "uri": "http://edamontology.org/topic_0780", "term": "Plants" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "Bologna Biocomputing Group" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "http://gpcr.biocomp.unibo.it/bacello", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btl222", "pmid": "16873501", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "BaCelLo: A balanced subcellular localization predictor", "abstract": "Motivation. The knowledge of the subcellular localization of a protein is fundamental for elucidating its function. It is difficult to determine the subcellular location for eukaryotic cells with experimental high-throughput procedures. Computational procedures are then needed for annotating the subcellular location of proteins in large scale genomic projects. Results. BaCelLo is a predictor for five classes of subcellular localization (secretory pathway, cytoplasm, nucleus, mitochondrion and chloroplast) and it is based on different SVMs organized in a decision tree. The system exploits the information derived from the residue sequence and from the evolutionary information contained in alignment profiles. It analyzes the whole sequence composition and the compositions of both the N- and C-termini. The training set is curated in order to avoid redundancy. For the first time a balancing procedure is introduced in order to mitigate the effect of biased training sets. Three kingdom-specific predictors are implemented: for animals, plants and fungi, respectively. When distributing the proteins from animals and fungi into four classes, accuracy of BaCelLo reach 74% and 76%, respectively; a score of 67% is obtained when proteins from plants are distributed into five classes. BaCelLo outperforms the other presently available methods for the same task and gives more balanced accuracy and coverage values for each class. We also predict the subcellular localization of five whole proteomes, Homo sapiens, Mus musculus, Caenorhabditis elegans, Saccharomyces cerevisiae and Arabidopsis thaliana, comparing the protein content in each different compartment. © 2006 Oxford University Press.", "date": "2006-07-15T00:00:00Z", "citationCount": 289, "authors": [ { "name": "Pierleoni A." }, { "name": "Martelli P.L." }, { "name": "Fariselli P." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "http://biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Division", "typeRole": [ "Provider" ], "note": null }, { "name": "Andrea Pierleoni", "email": "andrea@biocomp.unibo.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Pier Luigi Martelli", "email": "pierluigi.martelli@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-0274-5669", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null } ], "community": null, "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2015-01-22T11:31:34Z", "lastUpdate": "2024-03-15T09:43:37.278873Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "DeepSig", "description": "Prediction of secretory signal peptides in protein sequences", "homepage": "https://deepsig.biocomp.unibo.it", "biotoolsID": "deepsig", "biotoolsCURIE": "biotools:deepsig", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0418", "term": "Protein signal peptide detection" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] }, { "data": { "uri": "http://edamontology.org/data_3028", "term": "Taxonomy" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": null, "cmd": null } ], "toolType": [ "Web application", "Command-line tool" ], "topic": [ { "uri": "http://edamontology.org/topic_3307", "term": "Computational biology" }, { "uri": "http://edamontology.org/topic_3510", "term": "Protein sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0123", "term": "Protein properties" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": "GPL-3.0", "collectionID": [ "Bologna Biocomputing Group" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [ { "url": "https://deepsig.biocomp.unibo.it", "type": [ "Other" ], "note": null }, { "url": "https://github.com/BolognaBiocomp/deepsig", "type": [ "Other" ], "note": null } ], "download": [ { "url": "https://github.com/BolognaBiocomp/deepsig", "type": "Source code", "note": null, "version": "1.2.5" }, { "url": "https://hub.docker.com/r/bolognabiocomp/deepsig", "type": "Container file", "note": null, "version": null } ], "documentation": [ { "url": "https://github.com/BolognaBiocomp/deepsig", "type": [ "Command-line options" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btx818", "pmid": "29280997", "pmcid": "PMC5946842", "type": [ "Primary" ], "version": "1.0", "note": null, "metadata": { "title": "DeepSig: Deep learning improves signal peptide detection in proteins", "abstract": "Motivation The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization. Results Here, we present DeepSig, an improved approach for signal peptide detection and cleavage-site prediction based on deep learning methods. Comparative benchmarks performed on an updated independent dataset of proteins show that DeepSig is the current best performing method, scoring better than other available state-of-the-art approaches on both signal peptide detection and precise cleavage-site identification. Availability and implementation DeepSig is available as both standalone program and web server at https://deepsig.biocomp.unibo.it. All datasets used in this study can be obtained from the same website.", "date": "2018-05-15T00:00:00Z", "citationCount": 76, "authors": [ { "name": "Savojardo C." }, { "name": "Martelli P.L." }, { "name": "Fariselli P." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "http://biocomp.unibo.it", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": "http://biocomp.unibo.it/savojard", "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Pier Luigi Martelli", "email": "pierluigi.martelli@unibo.it", "url": "http://biocomp.unibo.it", "orcidid": "https://orcid.org/0000-0002-0274-5669", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2018-05-28T14:50:09Z", "lastUpdate": "2024-03-15T08:46:08.902943Z", "editPermission": { "type": "group", "authors": [ "savo", "ELIXIR-ITA-BOLOGNA" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "eDGAR", "description": "A database of Disease-Gene Associations with annotated Relationships among genes.", "homepage": "http://edgar.biocomp.unibo.it", "biotoolsID": "edgar", "biotoolsCURIE": "biotools:edgar", "version": [], "otherID": [ { "value": "doi:10.25504/FAIRsharing.29EHM2", "type": "doi", "version": null } ], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_3561", "term": "Database comparison" }, { "uri": "http://edamontology.org/operation_3197", "term": "Genetic variation analysis" }, { "uri": "http://edamontology.org/operation_2497", "term": "Pathway or network analysis" }, { "uri": "http://edamontology.org/operation_3672", "term": "Gene functional annotation" }, { "uri": "http://edamontology.org/operation_0276", "term": "Protein interaction network analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_3668", "term": "Disease name" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1622", "term": "Disease report" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": "For each heterogeneous or polygenic disease, eDGAR provides information on the relationship among the proteins encoded by the involved genes.", "cmd": null }, { "operation": [ { "uri": "http://edamontology.org/operation_3561", "term": "Database comparison" }, { "uri": "http://edamontology.org/operation_2497", "term": "Pathway or network analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_1153", "term": "OMIM ID" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1622", "term": "Disease report" }, "format": [ { "uri": "http://edamontology.org/format_3752", "term": "CSV" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": "For each heterogeneous or polygenic disease, eDGAR provides information on the relationship among the proteins encoded by the involved genes.", "cmd": null } ], "toolType": [ "Web application", "Database portal" ], "topic": [ { "uri": "http://edamontology.org/topic_0634", "term": "Pathology" }, { "uri": "http://edamontology.org/topic_3574", "term": "Human genetics" }, { "uri": "http://edamontology.org/topic_3325", "term": "Rare diseases" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "JavaScript" ], "license": "CC-BY-4.0", "collectionID": [ "RD-connect", "Rare Disease", "Bologna Biocomputing Group" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [ "Rare Diseases" ], "link": [], "download": [], "documentation": [ { "url": "http://edgar.biocomp.unibo.it/gene_disease_db/tutorial.html", "type": [ "User manual" ], "note": null } ], "publication": [ { "doi": "10.1186/s12864-017-3911-3", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "eDGAR: A database of disease-gene associations with annotated relationships among genes", "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.", "date": "2017-01-01T00:00:00Z", "citationCount": 45, "authors": [ { "name": "Babbi G." }, { "name": "Martelli P.L." }, { "name": "Profiti G." }, { "name": "Bovo S." }, { "name": "Savojardo C." }, { "name": "Casadio R." } ], "journal": "BMC Genomics" } } ], "credit": [ { "name": "Giulia Babbi", "email": "giulia.babbi3@unibo.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": "http://biocomp.unibo.it/", "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2017-03-13T17:04:55Z", "lastUpdate": "2024-03-14T13:58:52.828991Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-EE", "lmatalonga" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "Proteinortho", "description": "Proteinortho is a tool to detect orthologous genes within different species", "homepage": "https://gitlab.com/paulklemm_PHD/proteinortho", "biotoolsID": "proteinortho", "biotoolsCURIE": "biotools:proteinortho", "version": [ "6.3.1" ], "otherID": [], "relation": [ { "biotoolsID": "Diamond", "type": "uses" }, { "biotoolsID": "BLAST", "type": "uses" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0291", "term": "Sequence clustering" }, { "uri": "http://edamontology.org/operation_2403", "term": "Sequence analysis" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2976", "term": "Protein sequence" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_2048", "term": "Report" }, "format": [ { "uri": "http://edamontology.org/format_3475", "term": "TSV" }, { "uri": "http://edamontology.org/format_2331", "term": "HTML" }, { "uri": "http://edamontology.org/format_2332", "term": "XML" } ] } ], "note": null, "cmd": "proteinortho input/*.faa" } ], "toolType": [ "Command-line tool", "Workflow" ], "topic": [ { "uri": "http://edamontology.org/topic_0797", "term": "Comparative genomics" } ], "operatingSystem": [ "Linux", "Mac", "Windows" ], "language": [ "Perl", "C++", "Python" ], "license": "GPL-2.0", "collectionID": [], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [], "elixirCommunity": [], "link": [ { "url": "https://gitlab.com/paulklemm_PHD/proteinortho", "type": [ "Repository" ], "note": null }, { "url": "https://gitlab.com/paulklemm_PHD/proteinortho/-/issues?sort=created_date&state=opened", "type": [ "Issue tracker" ], "note": null }, { "url": "https://toolshed.g2.bx.psu.edu/repository?repository_id=584d8accff31aefe", "type": [ "Galaxy service" ], "note": null } ], "download": [ { "url": "https://gitlab.com/paulklemm_PHD/proteinortho/-/archive/master/proteinortho-master.zip", "type": "Source code", "note": "Download and unpack, compile with `make all`", "version": "latest" }, { "url": "https://packages.debian.org/unstable/proteinortho", "type": "Downloads page", "note": "Installation with dpkg (root privileges are required)", "version": null }, { "url": "https://anaconda.org/bioconda/proteinortho", "type": "Downloads page", "note": "conda install proteinortho", "version": null }, { "url": "https://formulae.brew.sh/formula/proteinortho", "type": "Downloads page", "note": "brew install proteinortho", "version": null } ], "documentation": [ { "url": "https://gitlab.com/paulklemm_PHD/proteinortho/-/releases", "type": [ "Release notes" ], "note": null }, { "url": "https://gitlab.com/paulklemm_PHD/proteinortho/-/wikis/home", "type": [ "FAQ" ], "note": null }, { "url": "https://gitlab.com/paulklemm_PHD/proteinortho", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.3389/fbinf.2023.1322477", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": "version 6", "note": "For the version 6 of proteinortho", "metadata": { "title": "Proteinortho6: pseudo-reciprocal best alignment heuristic for graph-based detection of (co-)orthologs", "abstract": "Proteinortho is a widely used tool to predict (co)-orthologous groups of genes for any set of species. It finds application in comparative and functional genomics, phylogenomics, and evolutionary reconstructions. With a rapidly increasing number of available genomes, the demand for large-scale predictions is also growing. In this contribution, we evaluate and implement major algorithmic improvements that significantly enhance the speed of the analysis without reducing precision. Graph-based detection of (co-)orthologs is typically based on a reciprocal best alignment heuristic that requires an all vs. all comparison of proteins from all species under study. The initial identification of similar proteins is accelerated by introducing an alternative search tool along with a revised search strategy—the pseudo-reciprocal best alignment heuristic—that reduces the number of required sequence comparisons by one-half. The clustering algorithm was reworked to efficiently decompose very large clusters and accelerate processing. Proteinortho6 reduces the overall processing time by an order of magnitude compared to its predecessor while maintaining its small memory footprint and good predictive quality.", "date": "2023-01-01T00:00:00Z", "citationCount": 0, "authors": [ { "name": "Klemm P." }, { "name": "Stadler P.F." }, { "name": "Lechner M." } ], "journal": "Frontiers in Bioinformatics" } }, { "doi": "10.1186/1471-2105-12-124", "pmid": "21526987", "pmcid": "PMC3114741", "type": [], "version": "version 4 to 5", "note": "For version 4 to 5 of proteinortho", "metadata": { "title": "Proteinortho: Detection of (Co-)orthologs in large-scale analysis", "abstract": "Background: Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases.Results: The program Proteinortho described here is a stand-alone tool that is geared towards large datasets and makes use of distributed computing techniques when run on multi-core hardware. It implements an extended version of the reciprocal best alignment heuristic. We apply Proteinortho to compute orthologous proteins in the complete set of all 717 eubacterial genomes available at NCBI at the beginning of 2009. We identified thirty proteins present in 99% of all bacterial proteomes.Conclusions: Proteinortho significantly reduces the required amount of memory for orthology analysis compared to existing tools, allowing such computations to be performed on off-the-shelf hardware. © 2011 Lechner et al; licensee BioMed Central Ltd.", "date": "2011-04-28T00:00:00Z", "citationCount": 799, "authors": [ { "name": "Lechner M." }, { "name": "Findeiss S." }, { "name": "Steiner L." }, { "name": "Marz M." }, { "name": "Stadler P.F." }, { "name": "Prohaska S.J." } ], "journal": "BMC Bioinformatics" } }, { "doi": "10.1371/journal.pone.0105015", "pmid": null, "pmcid": null, "type": [ "Other" ], "version": null, "note": "The synteny extension PoFF (-syteny option)", "metadata": { "title": "Orthology detection combining clustering and synteny for very large datasets", "abstract": "The elucidation of orthology relationships is an important step both in gene function prediction as well as towards understanding patterns of sequence evolution. Orthology assignments are usually derived directly from sequence similarities for large data because more exact approaches exhibit too high computational costs. Here we present PoFF, an extension for the standalone tool Proteinortho, which enhances orthology detection by combining clustering, sequence similarity, and synteny. In the course of this work, FFAdj-MCS, a heuristic that assesses pairwise gene order using adjacencies (a similarity measure related to the breakpoint distance) was adapted to support multiple linear chromosomes and extended to detect duplicated regions. PoFF largely reduces the number of false positives and enables more fine-grained predictions than purely similarity-based approaches. The extension maintains the low memory requirements and the efficient concurrency options of its basis Proteinortho, making the software applicable to very large datasets. © 2014 Lechner et al.", "date": "2014-08-19T00:00:00Z", "citationCount": 67, "authors": [ { "name": "Lechner M." }, { "name": "Hernandez-Rosales M." }, { "name": "Doerr D." }, { "name": "Wieseke N." }, { "name": "Thevenin A." }, { "name": "Stoye J." }, { "name": "Hartmann R.K." }, { "name": "Prohaska S.J." }, { "name": "Stadler P.F." } ], "journal": "PLoS ONE" } } ], "credit": [ { "name": "Marcus Lechner", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact", "Maintainer" ], "note": null }, { "name": "Paul Klemm", "email": null, "url": "https://gitlab.com/paulklemm", "orcidid": "https://orcid.org/0000-0002-3609-5713", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null } ], "community": null, "owner": "klemmp", "additionDate": "2022-03-22T18:57:49.937151Z", "lastUpdate": "2024-03-13T22:17:22.229211Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "TPpred 2.0", "description": "Mitochondrial targeting peptide prediction.", "homepage": "https://tppred2.biocomp.unibo.it", "biotoolsID": "tppred_2.0", "biotoolsCURIE": "biotools:tppred_2.0", "version": [ "2.0" ], "otherID": [], "relation": [ { "biotoolsID": "tppred_1.0", "type": "isNewVersionOf" }, { "biotoolsID": "tppred_3.0", "type": "hasNewVersion" } ], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2489", "term": "Protein subcellular localisation prediction" }, { "uri": "http://edamontology.org/operation_3092", "term": "Protein feature detection" }, { "uri": "http://edamontology.org/operation_0253", "term": "Sequence feature detection" }, { "uri": "http://edamontology.org/operation_0422", "term": "Protein cleavage site prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": "Prediction", "cmd": null } ], "toolType": [ "Command-line tool", "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0160", "term": "Sequence sites, features and motifs" }, { "uri": "http://edamontology.org/topic_0154", "term": "Small molecules" }, { "uri": "http://edamontology.org/topic_0140", "term": "Protein targeting and localisation" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [ "Python" ], "license": "GPL-3.0", "collectionID": [ "Bologna Biocomputing Group" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [ { "url": "http://biocomp.unibo.it/savojard/tppred2.tar.gz", "type": "Source code", "note": null, "version": null } ], "documentation": [ { "url": "https://tppred3.biocomp.unibo.it/tppred3/default/help", "type": [ "General" ], "note": null }, { "url": "https://tppred2.biocomp.unibo.it/tppred2/default/software", "type": [ "Command-line options" ], "note": "Installation instructions" } ], "publication": [ { "doi": "10.1093/bioinformatics/btu411", "pmid": "24974200", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": null }, { "doi": "10.1093/bioinformatics/btt089", "pmid": "23428638", "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "The prediction of organelle-targeting peptides in eukaryotic proteins with Grammatical-Restrained Hidden Conditional Random Fields", "abstract": "Motivation: Targeting peptides are the most important signal controlling the import of nuclear encoded proteins into mitochondria and plastids. In the lack of experimental information, their prediction is an essential step when proteomes are annotated for inferring both the localization and the sequence of mature proteins.Results: We developed TPpred a new predictor of organelle-targeting peptides based on Grammatical-Restrained Hidden Conditional Random Fields. TPpred is trained on a non-redundant dataset of proteins where the presence of a target peptide was experimentally validated, comprising 297 sequences. When tested on the 297 positive and some other 8010 negative examples, TPpred outperformed available methods in both accuracy and Matthews correlation index (96% and 0.58, respectively). Given its very low-false-positive rate (3.0%), TPpred is, therefore, well suited for large-scale analyses at the proteome level. We predicted that from ∼4 to 9% of the sequences of human, Arabidopsis thaliana and yeast proteomes contain targeting peptides and are, therefore, likely to be localized in mitochondria and plastids. TPpred predictions correlate to a good extent with the experimental annotation of the subcellular localization, when available. TPpred was also trained and tested to predict the cleavage site of the organelle-targeting peptide: on this task, the average error of TPpred on mitochondrial and plastidic proteins is 7 and 15 residues, respectively. This value is lower than the error reported by other methods currently available. © 2013 The Author.", "date": "2013-04-15T00:00:00Z", "citationCount": 14, "authors": [ { "name": "Indio V." }, { "name": "Martelli P.L." }, { "name": "Savojardo C." }, { "name": "Fariselli P." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Developer" ], "note": null }, { "name": "Rita Casadio", "email": "rita.casadio@unibo.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Piero Fariselli", "email": "piero.fariselli@unito.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null } ], "community": null, "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2016-01-22T15:53:12Z", "lastUpdate": "2024-03-11T16:57:44.699185Z", "editPermission": { "type": "group", "authors": [ "ELIXIR-ITA-BOLOGNA", "savo" ] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": "tool" }, { "name": "MemLoci", "description": "Predictor for the subcellular localization of proteins associated or inserted in eukaryotes membranes.", "homepage": "https://mu2py.biocomp.unibo.it/memloci", "biotoolsID": "memloci", "biotoolsCURIE": "biotools:memloci", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_2489", "term": "Protein subcellular localisation prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_1277", "term": "Protein features" }, "format": [ { "uri": "http://edamontology.org/format_2330", "term": "Textual format" } ] } ], "note": "Prediction", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0140", "term": "Protein targeting and localisation" }, { "uri": "http://edamontology.org/topic_0820", "term": "Membrane and lipoproteins" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "Bologna Biocomputing Group" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": "Open access", "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://mu2py.biocomp.unibo.it/memloci/default/info", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/bioinformatics/btr108", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "MemLoci: Predicting subcellular localization of membrane proteins in eukaryotes", "abstract": "Motivation: Subcellular localization is a key feature in the process of functional annotation of both globular and membrane proteins. In the absence of experimental data, protein localization is inferred on the basis of annotation transfer upon sequence similarity search. However, predictive tools are necessary when the localization of homologs is not known. This is so particularly for membrane proteins. Furthermore, most of the available predictors of subcellular localization are specifically trained on globular proteins and poorly perform on membrane proteins. Results: Here we develop MemLoci, a new support vector machinebased tool that discriminates three membrane protein localizations: plasma, internal and organelle membrane. When tested on an independent set, MemLoci outperforms existing methods, reaching an overall accuracy of 70% on predicting the location in the three membrane types, with a generalized correlation coefficient as high as 0.50. © The Author 2011. Published by Oxford University Press. All rights reserved.", "date": "2011-05-01T00:00:00Z", "citationCount": 47, "authors": [ { "name": "Pierleoni A." }, { "name": "Martelli P.L." }, { "name": "Casadio R." } ], "journal": "Bioinformatics" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Andrea Pierleoni", "email": "andrea@biocomp.unibo.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Pier Luigi Martelli", "email": "pierluigi.martelli@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-0274-5669", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null } ], "community": null, "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2015-01-22T11:31:40Z", "lastUpdate": "2024-03-11T16:57:20.943436Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null }, { "name": "MemPype", "description": "Prediction of topology and subcellular localization of Eukaryotic membrane proteins.", "homepage": "https://mu2py.biocomp.unibo.it/mempype", "biotoolsID": "mempype", "biotoolsCURIE": "biotools:mempype", "version": [ "1.0" ], "otherID": [], "relation": [], "function": [ { "operation": [ { "uri": "http://edamontology.org/operation_0468", "term": "Protein secondary structure prediction (helices)" }, { "uri": "http://edamontology.org/operation_0418", "term": "Protein signal peptide detection" }, { "uri": "http://edamontology.org/operation_0422", "term": "Protein cleavage site prediction" }, { "uri": "http://edamontology.org/operation_2489", "term": "Protein subcellular localisation prediction" } ], "input": [ { "data": { "uri": "http://edamontology.org/data_2974", "term": "Protein sequence (raw)" }, "format": [ { "uri": "http://edamontology.org/format_1929", "term": "FASTA" } ] } ], "output": [ { "data": { "uri": "http://edamontology.org/data_0896", "term": "Protein report" }, "format": [ { "uri": "http://edamontology.org/format_2331", "term": "HTML" } ] } ], "note": "Prediction", "cmd": null } ], "toolType": [ "Web application" ], "topic": [ { "uri": "http://edamontology.org/topic_0140", "term": "Protein targeting and localisation" }, { "uri": "http://edamontology.org/topic_0820", "term": "Membrane and lipoproteins" }, { "uri": "http://edamontology.org/topic_0621", "term": "Model organisms" } ], "operatingSystem": [ "Linux", "Windows", "Mac" ], "language": [], "license": null, "collectionID": [ "Bologna Biocomputing Group" ], "maturity": "Mature", "cost": "Free of charge", "accessibility": null, "elixirPlatform": [], "elixirNode": [ "Italy" ], "elixirCommunity": [], "link": [], "download": [], "documentation": [ { "url": "https://mu2py.biocomp.unibo.it/mempype/default/help", "type": [ "General" ], "note": null } ], "publication": [ { "doi": "10.1093/nar/gkr282", "pmid": null, "pmcid": null, "type": [ "Primary" ], "version": null, "note": null, "metadata": { "title": "MemPype: A pipeline for the annotation of eukaryotic membrane proteins", "abstract": "MemPype is a Python-based pipeline including previously published methods for the prediction of signal peptides (SPEP), glycophosphatidylinositol (GPI) anchors (PredGPI), all-alpha membrane topology (ENSEMBLE), and a recent method (MemLoci) that specifically discriminates the localization of eukaryotic membrane proteins in: 'cell membrane', 'internal membranes', 'organelle membranes'. MemLoci scores with accuracy of 70 and generalized correlation coefficient (GCC) of 0.50 on a rigorous homology-unbiased validation set and overpasses other predictors for subcellular localization. The annotation process is based both on inheritance through homology and computational methods. Each submitted protein first retrieves, when available, up to 25 similar proteins (with sequence identity ≥50 and alignment coverage ≥50 on both sequences). This helps the identification of membrane-associated proteins and detailed localization tags. Each protein is also filtered for the presence of a GPI anchor [0.8 false positive rate (FPR)]. A positive score of GPI anchor prediction labels the sequence as exposed to 'Cell surface'. Concomitantly the sequence is analysed for the presence of a signal peptide and classified with MemLoci into one of three discriminated classes. Finally the sequence is filtered for predicting its putative all-alpha protein membrane topology (FPR<1). The web server is available at: http://mu2py.biocomp.unibo.it/ mempype. © 2011 The Author(s).", "date": "2011-07-01T00:00:00Z", "citationCount": 27, "authors": [ { "name": "Pierleoni A." }, { "name": "Indio V." }, { "name": "Savojardo C." }, { "name": "Fariselli P." }, { "name": "Martelli P.L." }, { "name": "Casadio R." } ], "journal": "Nucleic Acids Research" } } ], "credit": [ { "name": "ELIXIR-ITA-BOLOGNA", "email": null, "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Institute", "typeRole": [ "Provider" ], "note": null }, { "name": "Andrea Pierleoni", "email": "andrea@biocomp.unibo.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Pier Luigi Martelli", "email": "pierluigi.martelli@unibo.it", "url": null, "orcidid": null, "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Primary contact" ], "note": null }, { "name": "Castrense Savojardo", "email": "castrense.savojardo2@unibo.it", "url": null, "orcidid": "https://orcid.org/0000-0002-7359-0633", "gridid": null, "rorid": null, "fundrefid": null, "typeEntity": "Person", "typeRole": [ "Maintainer" ], "note": null } ], "community": null, "owner": "ELIXIR-ITA-BOLOGNA", "additionDate": "2015-01-22T11:31:40Z", "lastUpdate": "2024-03-11T16:56:43.617506Z", "editPermission": { "type": "private", "authors": [] }, "validated": 1, "homepage_status": 0, "elixir_badge": 0, "confidence_flag": null } ] }{ "count": 7316, "next": "?page=2", "previous": null, "list": [ { "name": "PanEffect", "description": "A pan-genome visualization tool for variant effects in maize.", "homepage": "