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XLinkDB 2.0: integrated, large-scale structural analysis of protein crosslinking data.
Schweppe, Devin K; Zheng, Chunxiang; Chavez, Juan D; Navare, Arti T; Wu, Xia; Eng, Jimmy K; Bruce, James E.
Afiliación
  • Schweppe DK; Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
  • Zheng C; Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
  • Chavez JD; Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
  • Navare AT; Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
  • Wu X; Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
  • Eng JK; University of Washington Proteomics Resource, Seattle, WA 98109, USA.
  • Bruce JE; Department of Genome Sciences, University of Washington, Seattle, WA 98109, USA.
Bioinformatics ; 32(17): 2716-8, 2016 09 01.
Article en En | MEDLINE | ID: mdl-27153666
ABSTRACT
MOTIVATION Large-scale chemical cross-linking with mass spectrometry (XL-MS) analyses are quickly becoming a powerful means for high-throughput determination of protein structural information and protein-protein interactions. Recent studies have garnered thousands of cross-linked interactions, yet the field lacks an effective tool to compile experimental data or access the network and structural knowledge for these large scale analyses. We present XLinkDB 2.0 which integrates tools for network analysis, Protein Databank queries, modeling of predicted protein structures and modeling of docked protein structures. The novel, integrated approach of XLinkDB 2.0 enables the holistic analysis of XL-MS protein interaction data without limitation to the cross-linker or analytical system used for the analysis. AVAILABILITY AND IMPLEMENTATION XLinkDB 2.0 can be found here, including documentation and help http//xlinkdb.gs.washington.edu/ CONTACT jimbruce@uw.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Conformación Proteica / Programas Informáticos / Proteínas / Bases de Datos de Proteínas Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Conformación Proteica / Programas Informáticos / Proteínas / Bases de Datos de Proteínas Tipo de estudio: Prognostic_studies Límite: Humans Idioma: En Revista: Bioinformatics Asunto de la revista: INFORMATICA MEDICA Año: 2016 Tipo del documento: Article País de afiliación: Estados Unidos