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• W2017117968 abstract "Detecting protein complexes from protein-protein interaction (PPI) network is becoming a difficult challenge in computational biology. Observations show that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein or functional interactions. This paper introduces a novel method for detecting protein-complexes from PPI by using a protein ranking algorithm (ProRank) and incorporating an evolutionary relationships between proteins in the network. The method successfully predicted 57 out of 81 benchmarked protein complexes created from the Munich Information Center for Protein Sequence (MIPS). The level of the accuracy achieved using ProRank in comparison to other recent methods for detecting protein complexes is a strong argument in favor of our proposed method. Datasets, programs and results are available at http://faculty.uaeu.ac.ae/nzaki/ProRank.htm." @default.
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• W2017117968 date "2012-07-07" @default.
• W2017117968 modified "2023-09-26" @default.
• W2017117968 title "ProRank" @default.
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• W2017117968 doi "https://doi.org/10.1145/2330163.2330193" @default.
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