• Methods Mol. Biol. · Jan 2017

    iPTMnet: Integrative Bioinformatics for Studying PTM Networks.

    • Karen E Ross, Hongzhan Huang, Jia Ren, Cecilia N Arighi, Gang Li, Catalina O Tudor, Mengxi Lv, Jung-Youn Lee, Sheng-Chih Chen, K Vijay-Shanker, and Cathy H Wu.
    • Department of Biochemistry and Molecular and Cellular Biology, Georgetown University Medical Center, 3300 Whitehaven Street NW, Suite 1200, Washington, DC, 20057, USA. ker25@georgetown.edu.
    • Methods Mol. Biol. 2017 Jan 1; 1558: 333-353.

    AbstractProtein post-translational modification (PTM) is an essential cellular regulatory mechanism, and disruptions in PTM have been implicated in disease. PTMs are an active area of study in many fields, leading to a wealth of PTM information in the scientific literature. There is a need for user-friendly bioinformatics resources that capture PTM information from the literature and support analyses of PTMs and their functional consequences. This chapter describes the use of iPTMnet ( http://proteininformationresource.org/iPTMnet/ ), a resource that integrates PTM information from text mining, curated databases, and ontologies and provides visualization tools for exploring PTM networks, PTM crosstalk, and PTM conservation across species. We present several PTM-related queries and demonstrate how they can be addressed using iPTMnet.

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