%0 Generic %A Wu, Min %A Li, Xiaoli %A Kwoh, Chee-Keong %D 2017 %T Algorithms for detecting protein complexes in PPI networks: an evaluation study %U https://bridges.monash.edu/articles/dataset/Algorithms_for_detecting_protein_complexes_in_PPI_networks_an_evaluation_study/5619499 %R 10.4225/03/5a137247533fb %2 https://bridges.monash.edu/ndownloader/files/9783253 %K Bioinformatics -- Congresses %K Computational biology -- Congresses %K Computer vision in medicine -- Congresses %K Computational biology -- Methods -- Congresses %K Pattern recognition, automated -- Methods -- Congresses %K 2008 %K conference paper %K 1959.1/63703 %K monash:7859 %K Bioinformatics Software %K Bioinformatics %K Pattern Recognition and Data Mining %X 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[2], MCL[21], CPA[1] and DECAFF[14]) 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. %I Monash University