Please use this identifier to cite or link to this item: https://doi.org/10.1002/pmic.201100508
Title: Computational detection of protein complexes in AP-MS experiments
Authors: Choi, H. 
Keywords: Bioinformatics
Interaction profiling
Protein-protein complexes
Systems biology
Issue Date: May-2012
Source: Choi, H. (2012-05). Computational detection of protein complexes in AP-MS experiments. Proteomics 12 (10) : 1663-1668. ScholarBank@NUS Repository. https://doi.org/10.1002/pmic.201100508
Abstract: Protein complex identification is an important goal of protein-protein interaction analysis. To date, development of computational methods for detecting protein complexes has been largely motivated by genome-scale interaction data sets from high-throughput assays such as yeast two-hybrid or tandem affinity purification coupled with mass spectrometry (TAP-MS). However, due to the popularity of small to intermediate-scale affinity purification-mass spectrometry (AP-MS) experiments, protein complex detection is increasingly discussed in local network analysis. In such data sets, protein complexes cannot be detected using binary interaction data alone because the data contain interactions with tagged proteins only and, as a result, interactions between all other proteins remain unobserved, limiting the scope of existing algorithms. In this article, we provide a pragmatic review of network graph-based computational algorithms for protein complex analysis in global interactome data, without requiring any computational background. We discuss the practical gap in applying these algorithms to recently surging small to intermediate-scale AP-MS data sets, and review alternative clustering algorithms using quantitative proteomics data and their limitations. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Source Title: Proteomics
URI: http://scholarbank.nus.edu.sg/handle/10635/109110
ISSN: 16159853
DOI: 10.1002/pmic.201100508
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