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XLinkDB 2.0: integrated, large-scale structural analysis of protein crosslinking data
Author(s) -
Devin K. Schweppe,
Chunxiang Zheng,
Juan D. Chavez,
Arti Navare,
Xia Wu,
Jimmy K. Eng,
James E. Bruce
Publication year - 2016
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btw232
Subject(s) - computer science , documentation , scale (ratio) , field (mathematics) , compiler , data mining , protein–protein interaction , protein structure , computational biology , chemistry , programming language , biology , biochemistry , physics , mathematics , quantum mechanics , pure mathematics
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.

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