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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/15428

Title: Mining Minimal Motif Pair Sets Maximally Covering Interactions in a Protein-Protein Interaction Network
Authors: BOYEN, Peter
NEVEN, Frank
VAN DYCK, Dries
Valentim, Felipe L.
van Dijk, Aalt D. J.
Issue Date: 2013
Publisher: IEEE COMPUTER SOC
Citation: IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 10 (1), p. 73-86
Abstract: Correlated motif covering (CMC) is the problem of finding a set of motif pairs, i.e., pairs of patterns, in the sequences of proteins from a protein-protein interaction network (PPI-network) that describe the interactions in the network as concisely as possible. In other words, a perfect solution for CMC would be a minimal set of motif pairs that describes the interaction behavior perfectly in the sense that two proteins from the network interact if and only if their sequences match a motif pair in the minimal set. In this paper, we introduce and formally define CMC and show that it is closely related to the red-blue set cover (RBSC) problem and its weighted version (WRBSC)-both well-known NP-hard problems for that there exist several algorithms with known approximation factor guarantees. We prove the hardness of approximation of CMC by providing an approximation factor preserving reduction from RBSC to CMC. We show the existence of a theoretical approximation algorithm for CMC by providing an approximation factor preserving reduction from CMC to WRBSC. We adapt the latter algorithm into a functional heuristic for CMC, called CMC-approx, and experimentally assess its performance and biological relevance. The implementation in Java can be found at http://bioinformatics.uhasselt.be.
Notes: Boyen, P (reprint author), Hasselt Univ, B-3590 Diepenbeek, Belgium. Transnat Univ Limburg, B-3590 Diepenbeek, Belgium. Belgian Nucl Res Ctr SCK CEN, B-2400 Mol, Belgium. Plant Res Int, Appl Bioinformat, NL-6708 PB Wageningen, Netherlands. peter.boyen@uhasselt.be
URI: http://hdl.handle.net/1942/15428
DOI: 10.1109/TCBB.2012.165
ISI #: 000319477300008
ISSN: 1545-5963
Category: A1
Type: Journal Contribution
Validation: ecoom, 2014
Appears in Collections: Research publications

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