title: A binary matrix factorization algorithm for protein complex prediction.
abstract: BACKGROUND
  Identifying biologically relevant protein complexes from a large protein-protein interaction (PPI) network, is essential to understand the organization of biological systems. However, high-throughput experimental techniques that can produce a large amount of PPIs are known to yield non-negligible rates of false-positives and false-negatives, making the protein complexes difficult to be identified.
  
  
  RESULTS
  We propose a binary matrix factorization (BMF) algorithm under the Bayesian Ying-Yang (BYY) harmony learning, to detect protein complexes by clustering the proteins which share similar interactions through factorizing the binary adjacent matrix of a PPI network. The proposed BYY-BMF algorithm automatically determines the cluster number while this number is pre-given for most existing BMF algorithms. Also, BYY-BMF's clustering results does not depend on any parameters or thresholds, unlike the Markov Cluster Algorithm (MCL) that relies on a so-called inflation parameter. On synthetic PPI networks, the predictions evaluated by the known annotated complexes indicate that BYY-BMF is more robust than MCL for most cases. On real PPI networks from the MIPS and DIP databases, BYY-BMF obtains a better balanced prediction accuracies than MCL and a spectral analysis method, while MCL has its own advantages, e.g., with good separation values.
authors.affiliation: Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
authors.forename: Shikui
authors.initials: S
authors.lastname: Tu
authors.affiliation: Bioinformatics Laboratory and National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101.
authors.forename: Runsheng
authors.initials: R
authors.lastname: Chen
authors.affiliation: Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong.
authors.forename: Lei
authors.initials: L
authors.lastname: Xu