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iPTMnet: an integrated resource for protein post-translational modification network discovery.
Huang, Hongzhan; Arighi, Cecilia N; Ross, Karen E; Ren, Jia; Li, Gang; Chen, Sheng-Chih; Wang, Qinghua; Cowart, Julie; Vijay-Shanker, K; Wu, Cathy H.
Afiliación
  • Huang H; Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE 19711, USA.
  • Arighi CN; Department of Computer & Information Sciences, University of Delaware, Newark, DE 19711, USA.
  • Ross KE; Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE 19711, USA.
  • Ren J; Department of Computer & Information Sciences, University of Delaware, Newark, DE 19711, USA.
  • Li G; Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC 20057, USA.
  • Chen SC; Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE 19711, USA.
  • Wang Q; Department of Computer & Information Sciences, University of Delaware, Newark, DE 19711, USA.
  • Cowart J; Department of Computer & Information Sciences, University of Delaware, Newark, DE 19711, USA.
  • Vijay-Shanker K; Center for Bioinformatics and Computational Biology, University of Delaware, Newark, DE 19711, USA.
  • Wu CH; Department of Computer & Information Sciences, University of Delaware, Newark, DE 19711, USA.
Nucleic Acids Res ; 46(D1): D542-D550, 2018 01 04.
Article en En | MEDLINE | ID: mdl-29145615
Protein post-translational modifications (PTMs) play a pivotal role in numerous biological processes by modulating regulation of protein function. We have developed iPTMnet (http://proteininformationresource.org/iPTMnet) for PTM knowledge discovery, employing an integrative bioinformatics approach-combining text mining, data mining, and ontological representation to capture rich PTM information, including PTM enzyme-substrate-site relationships, PTM-specific protein-protein interactions (PPIs) and PTM conservation across species. iPTMnet encompasses data from (i) our PTM-focused text mining tools, RLIMS-P and eFIP, which extract phosphorylation information from full-scale mining of PubMed abstracts and full-length articles; (ii) a set of curated databases with experimentally observed PTMs; and iii) Protein Ontology that organizes proteins and PTM proteoforms, enabling their representation, annotation and comparison within and across species. Presently covering eight major PTM types (phosphorylation, ubiquitination, acetylation, methylation, glycosylation, S-nitrosylation, sumoylation and myristoylation), iPTMnet knowledgebase contains more than 654 500 unique PTM sites in over 62 100 proteins, along with more than 1200 PTM enzymes and over 24 300 PTM enzyme-substrate-site relations. The website supports online search, browsing, retrieval and visual analysis for scientific queries. Several examples, including functional interpretation of phosphoproteomic data, demonstrate iPTMnet as a gateway for visual exploration and systematic analysis of PTM networks and conservation, thereby enabling PTM discovery and hypothesis generation.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento Proteico-Postraduccional / Bases de Datos de Proteínas / Bases del Conocimiento Tipo de estudio: Systematic_reviews Límite: Animals / Humans Idioma: En Revista: Nucleic Acids Res Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Procesamiento Proteico-Postraduccional / Bases de Datos de Proteínas / Bases del Conocimiento Tipo de estudio: Systematic_reviews Límite: Animals / Humans Idioma: En Revista: Nucleic Acids Res Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos