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Methods Mol Biol. 2017;1549:147-161.

Bioinformatics Methods to Deduce Biological Interpretation from Proteomics Data.

Author information

1
Institute of Bioinformatics, Discoverer Building, International Technology Park, Whitefield, Bangalore, 560066, India.
2
Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Kollam, India.
3
Institute of Bioinformatics, Discoverer Building, International Technology Park, Whitefield, Bangalore, 560066, India. harsha@ibioinformatics.org.
4
YU-IOB Center for Systems Biology and Molecular Medicine, Yenepoya University, Mangalore, India. harsha@ibioinformatics.org.

Abstract

High-throughput proteomics studies generate large amounts of data. Biological interpretation of these large scale datasets is often challenging. Over the years, several computational tools have been developed to facilitate meaningful interpretation of large-scale proteomics data. In this chapter, we describe various analyses that can be performed and bioinformatics tools and resources that enable users to do the analyses. Many Web-based and stand-alone tools are relatively user-friendly and can be used by most biologists without significant assistance.

KEYWORDS:

Enrichment; FunRich; Gene ontology; NetPath; Pathways; Phosphoproteome; Post-translational modifications; Reactome

PMID:
27975290
DOI:
10.1007/978-1-4939-6740-7_12
[Indexed for MEDLINE]

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