Algorithms for detecting protein complexes in PPI networks: an evaluation study
datasetposted on 21.11.2017, 00:24 authored by Wu, Min, Li, Xiaoli, Kwoh, Chee-Keong
Since protein complexes play important biological roles in cells, many computational methods have been proposed to detect protein complexes from protein-protein interaction (PPI) data. In this paper, we first review four reputed protein-complex detection algorithms (MCODE, MCL, CPA and DECAFF) and then present a comprehensive evaluation among them on two popular yeast PPI data3. We also discuss their relative strengthes and disadvantages to guide interested researchers. PRIB 2008 proceedings found at: http://dx.doi.org/10.1007/978-3-540-88436-1 Contributors: Monash University. Faculty of Information Technology. Gippsland School of Information Technology ; Chetty, Madhu ; Ahmad, Shandar ; Ngom, Alioune ; Teng, Shyh Wei ; Third IAPR International Conference on Pattern Recognition in Bioinformatics (PRIB) (3rd : 2008 : Melbourne, Australia) ; Coverage: Rights: Copyright by Third IAPR International Conference on Pattern Recognition in Bioinformatics. All rights reserved.
Bioinformatics -- CongressesComputational biology -- CongressesComputer vision in medicine -- CongressesComputational biology -- Methods -- CongressesPattern recognition, automated -- Methods -- Congresses2008conference paper1959.1/63703monash:7859Bioinformatics SoftwareBioinformaticsPattern Recognition and Data Mining