CSDL Home IEEE/ACM Transactions on Computational Biology and Bioinformatics 2013 vol.10 Issue No.01 - Jan.-Feb.

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Issue No.01 - Jan.-Feb. (2013 vol.10)

pp: 73-86

Peter Boyen , Hasselt Univ. & Transnat., Univ. of Limburg, Diepenbeek, Belgium

Frank Neven , Hasselt Univ. & Transnat., Univ. of Limburg, Diepenbeek, Belgium

Dries van Dyck , Adv. Nucl. Syst., Nucl. Syst. Res., Belgian Nucl. Res. Centre (SCK-CEN), Mol, Belgium

Felipe L. Valentim , Appl. Bioinf., Plant Res. Int., Wageningen, Netherlands

Aalt D. J. van Dijk , Appl. Bioinf., Plant Res. Int., Wageningen, Netherlands

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/TCBB.2012.165

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.

INDEX TERMS

Proteins, Approximation methods, Approximation algorithms, Bioinformatics, Silicon, IEEE transactions,local search, Graphs and networks, biology and genetics, correlated motifs, PPI networks

CITATION

Peter Boyen, Frank Neven, Dries van Dyck, Felipe L. Valentim, Aalt D. J. van Dijk, "Mining Minimal Motif Pair Sets Maximally Covering Interactions in a Protein-Protein Interaction Network",

*IEEE/ACM Transactions on Computational Biology and Bioinformatics*, vol.10, no. 1, pp. 73-86, Jan.-Feb. 2013, doi:10.1109/TCBB.2012.165REFERENCES