CoBaltDB: Complete bacterial and archaeal orfeomes subcellular localization database and associated resources
| Autor: | Frédérique Barloy-Hubler, David Goudenège, Stéphane Avner, Céline Lucchetti-Miganeh |
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| Přispěvatelé: | Interactions cellulaires et moléculaires (ICM), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS) |
| Jazyk: | angličtina |
| Rok vydání: | 2010 |
| Předmět: |
Microbiology (medical)
Signal peptide Interface (Java) In silico lcsh:QR1-502 Information Storage and Retrieval Locus (genetics) Biology computer.software_genre Microbiology lcsh:Microbiology Genes Archaeal Database 03 medical and health sciences Open Reading Frames User-Computer Interface Software Databases Genetic Computer Simulation [SDV.BBM]Life Sciences [q-bio]/Biochemistry Molecular Biology 030304 developmental biology 0303 health sciences 030306 microbiology business.industry Computational Biology Protein subcellular localization prediction Task (computing) ComputingMethodologies_PATTERNRECOGNITION Genes Bacterial Proteome Database Management Systems business computer |
| Zdroj: | BMC Microbiology BMC Microbiology, BioMed Central, 2010, 10, pp.88. ⟨10.1186/1471-2180-10-88⟩ BMC Microbiology, Vol 10, Iss 1, p 88 (2010) BMC Microbiology, 2010, 10, pp.88. ⟨10.1186/1471-2180-10-88⟩ |
| ISSN: | 1471-2180 |
| DOI: | 10.1186/1471-2180-10-88⟩ |
| Popis: | BackgroundThe functions of proteins are strongly related to their localization in cell compartments (for example the cytoplasm or membranes) but the experimental determination of the sub-cellular localization of proteomes is laborious and expensive. A fast and low-cost alternative approach isin silicoprediction, based on features of the protein primary sequences. However, biologists are confronted with a very large number of computational tools that use different methods that address various localization features with diverse specificities and sensitivities. As a result, exploiting these computer resources to predict protein localization accurately involves querying all tools and comparing every prediction output; this is a painstaking task. Therefore, we developed a comprehensive database, called CoBaltDB, that gathers all prediction outputs concerning complete prokaryotic proteomes.DescriptionThe current version of CoBaltDB integrates the results of 43 localization predictors for 784 complete bacterial and archaeal proteomes (2.548.292 proteins in total). CoBaltDB supplies a simple user-friendly interface for retrieving and exploring relevant information about predicted features (such as signal peptide cleavage sites and transmembrane segments). Data are organized into three work-sets ("specialized tools", "meta-tools" and "additional tools"). The database can be queried using the organism name, a locus tag or a list of locus tags and may be browsed using numerous graphical and text displays.ConclusionsWith its new functionalities, CoBaltDB is a novel powerful platform that provides easy access to the results of multiple localization tools and support for predicting prokaryotic protein localizations with higher confidence than previously possible. CoBaltDB is available athttp://www.umr6026.univ-rennes1.fr/english/home/research/basic/software/cobalten. |
| Databáze: | OpenAIRE |
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