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A three-phase method for identifying functionally related protein groups in weighted PPI networks
Institution:1. University of Banjaluka, Faculty of Natural Sciences and Mathematics, Mladena Stojanovića 2, 78000 Banjaluka, Bosnia and Herzegovina;2. University of Belgrade, Faculty of Mathematics, Studentski trg 16/IV 11 000, Belgrade, Serbia
Abstract:Identifying significant protein groups is of great importance for further understanding protein functions. This paper introduces a novel three-phase heuristic method for identifying such groups in weighted PPI networks. In the first phase a variable neighborhood search (VNS) algorithm is applied on a weighted PPI network, in order to support protein complexes by adding a minimum number of new PPIs. In the second phase proteins from different complexes are merged into larger protein groups. In the third phase these groups are expanded by a number of 2-level neighbor proteins, favoring proteins that have higher average gene co-expression with the base group proteins. Experimental results show that: (i) the proposed VNS algorithm outperforms the existing approach described in literature and (ii) the above-mentioned three-phase method identifies protein groups with very high statistical significance.
Keywords:Weighted PPI networks  Protein groups  Variable neighborhood search  Gene co-expression
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