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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/22782

Title: Protein complex analysis: From raw protein lists to protein interaction networks
Authors: Meysman, Pieter
Titeca, Kevin
Eyckerman, Sven
Tavernier, Jan
Goethals, Bart
Martens, Lennart
Valkenborg, Dirk
Laukens, Kris
Issue Date: 2015
Citation: MASS SPECTROMETRY REVIEWS, 36 (5), p. 600-614
Status: In Press
Abstract: The elucidation of molecular interaction networks is one of the pivotal challenges in the study of biology. Affinity purification—mass spectrometry and other co-complex methods have become widely employed experimental techniques to identify protein complexes. These techniques typically suffer from a high number of false negatives and false positive contaminants due to technical shortcomings and purification biases. To support a diverse range of experimental designs and approaches, a large number of computational methods have been proposed to filter, infer and validate protein interaction networks from experimental pull-down MS data. Nevertheless, this expansion of available methods complicates the selection of the most optimal ones to support systems biology-driven knowledge extraction. In this review, we give an overview of the most commonly used computational methods to process and interpret co-complex results, and we discuss the issues and unsolved problems that still exist within the field
Notes: Meysman, P (reprint author), Univ Antwerp, Dept Math & Comp Sci, ADReM, Middelheimlaan 1, Antwerp, Belgium. pieter.meysman@uantwerpen.be
URI: http://hdl.handle.net/1942/22782
DOI: 10.1002/mas.21485
ISI #: 000407931000003
ISSN: 0277-7037
Category: A1
Type: Journal Contribution
Appears in Collections: Research publications

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