Data Mining in Protein Identification by Tandem Mass Spectrometry

View Sample PDF

Author(s): Haipeng Wang (Institute of Computing Technology & Graduate University of Chinese Academy of Sciences, China)
Copyright: 2009
Pages: 7
Source title: Encyclopedia of Data Warehousing and Mining, Second Edition
Source Author(s)/Editor(s): John Wang (Montclair State University, USA)
DOI: 10.4018/978-1-60566-010-3.ch074

Purchase

View Data Mining in Protein Identification by Tandem Mass Spectrometry on the publisher's website for pricing and purchasing information.

Abstract

Protein identification (sequencing) by tandem mass spectrometry is a fundamental technique for proteomics which studies structures and functions of proteins in large scale and acts as a complement to genomics. Analysis and interpretation of vast amounts of spectral data generated in proteomics experiments present unprecedented challenges and opportunities for data mining in areas such as data preprocessing, peptide-spectrum matching, results validation, peptide fragmentation pattern discovery and modeling, and post-translational modification (PTM) analysis. This article introduces the basic concepts and terms of protein identification and briefly reviews the state-of-the-art relevant data mining applications. It also outlines challenges and future potential hot spots in this field.

The IRMA Community

Research IRM

Data Mining in Protein Identification by Tandem Mass Spectrometry

Purchase

Abstract

Related Content

IRMA Sponsors