Integrated Bioinformatics Analysis of the Publicly Available Protein Data Shows Evidence for 96% of the Human Proteome
Department of Biochemistry, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Victoria 3086, Australia
- *Corresponding Author:
- Suresh Mathivanan
Department of Biochemistry, La Trobe Institute for Molecular Science
La Trobe University, Bundoora, Victoria 3086, Australia
Tel: +61 03 9479 2565
Fax: +61 03 9479 1226
E-mail: [email protected]
Received Date: December 11, 2013; Accepted Date: February 17, 2014; Published Date: February 20, 2014
Citation: Mathivanan S (2014) Integrated Bioinformatics Analysis of the Publicly Available Protein Data Shows Evidence for 96% of the Human Proteome. J Proteomics Bioinform 7: 041-049. doi: 10.4172/jpb.1000301
Copyright: © 2014 Mathivanan S. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Protein-coding genes are predicted by genome annotation pipelines and are conceptually translated into protein sequences. Several thousands of these protein-coding genes catalogued in publicly-available databases seldom have evidence at the protein level. In this study, we have created a map of the human proteome by integrating publicly-available proteomic studies and resources. With the encompassed data, we are able to map 96% of the human proteome with ample experimental evidence for protein expression. Over 2.2 million annotations are recorded for 19,716 proteins from 63,239 independent studies that utilized more than 800 tissue/cell types/body fluids. Among the mapped human proteome, 96% of the protein expression is supported by two or more independent studies or experimental methods. The collated data (localization, tissue expression, post-translational modifications, proteinprotein interactions, enzymes-substrate and 3D structures) is freely accessible through the web-based compendium Human Proteome Browser (https://www.humanproteomebrowser.info).