question: List algorithms suitable for predicting protein complexes
answer: Protein-Protein interactions (PPI) play a key role in determining the outcome of most cellular processes. The correct identification and characterization of protein interactions and the networks, which they comprise, is critical for understanding the molecular mechanisms within the cell. Large-scale techniques such as pull down assays and tandem affinity purification are used in order to detect protein interactions in an organism. Today, relatively new high-throughput methods like yeast two hybrid, mass spectrometry, microarrays, and phage display are also used to reveal protein interaction networks. Some suitable algorithms for predicting protein complexes are Naive Bayes Classifier, Negatome, Support Vector Machine, PEWCC, iPTMClust, NDComplex, PROCOMOSS, PPI network, metaPIS, EPOF, EAGLE, NFC, MCODE, DPClus, IPCA, CPM, MCL, CMC, SPICi, Core-Attachment, ProRank, ClusterONE, CFinder, Spectral, RNSC, Affinity Propagation, HKC, NWE, CP-DR, Struct2net and PIPE.