title: A new method to improve network topological similarity search: applied to fold recognition.
abstract: BACKGROUND
  Similarity search is the foundation of bioinformatics. It plays a key role in establishing structural, functional and evolutionary relationships between biological sequences. Although the power of the similarity search has increased steadily in recent years, a high percentage of sequences remain uncharacterized in the protein universe. Thus, new similarity search strategies are needed to efficiently and reliably infer the structure and function of new sequences. The existing paradigm for studying protein sequence, structure, function and evolution has been established based on the assumption that the protein universe is discrete and hierarchical. Cumulative evidence suggests that the protein universe is continuous. As a result, conventional sequence homology search methods may be not able to detect novel structural, functional and evolutionary relationships between proteins from weak and noisy sequence signals. To overcome the limitations in existing similarity search methods, we propose a new algorithmic framework-Enrichment of Network Topological Similarity (ENTS)-to improve the performance of large scale similarity searches in bioinformatics.
  
  
  RESULTS
  We apply ENTS to a challenging unsolved problem: protein fold recognition. Our rigorous benchmark studies demonstrate that ENTS considerably outperforms state-of-the-art methods. As the concept of ENTS can be applied to any similarity metric, it may provide a general framework for similarity search on any set of biological entities, given their representation as a network.
  
  
  METHODS
  Source code freely available upon request
  
  
  BACKGROUND
  : lxie@iscb.org.
authors.affiliation: Hunter College High School, New York, NY 10128, U.S.A., Department of Computer Science, Hunter College, The City University of New York, New York, NY 10065, U.S.A., Department of Biological Sciences, Hunter College, The City University of New York New York, NY 10065, U.S.A. and The Graduate Center, The City University of New York, New York, NY 10016, U.S.A.
authors.forename: John
authors.initials: J
authors.lastname: Lhota
authors.affiliation: Hunter College High School, New York, NY 10128, U.S.A., Department of Computer Science, Hunter College, The City University of New York, New York, NY 10065, U.S.A., Department of Biological Sciences, Hunter College, The City University of New York New York, NY 10065, U.S.A. and The Graduate Center, The City University of New York, New York, NY 10016, U.S.A.
authors.forename: Ruth
authors.initials: R
authors.lastname: Hauptman
authors.affiliation: Hunter College High School, New York, NY 10128, U.S.A., Department of Computer Science, Hunter College, The City University of New York, New York, NY 10065, U.S.A., Department of Biological Sciences, Hunter College, The City University of New York New York, NY 10065, U.S.A. and The Graduate Center, The City University of New York, New York, NY 10016, U.S.A.
authors.forename: Thomas
authors.initials: T
authors.lastname: Hart
authors.affiliation: Hunter College High School, New York, NY 10128, U.S.A., Department of Computer Science, Hunter College, The City University of New York, New York, NY 10065, U.S.A., Department of Biological Sciences, Hunter College, The City University of New York New York, NY 10065, U.S.A. and The Graduate Center, The City University of New York, New York, NY 10016, U.S.A.
authors.forename: Clara
authors.initials: C
authors.lastname: Ng
authors.affiliation: Hunter College High School, New York, NY 10128, U.S.A., Department of Computer Science, Hunter College, The City University of New York, New York, NY 10065, U.S.A., Department of Biological Sciences, Hunter College, The City University of New York New York, NY 10065, U.S.A. and The Graduate Center, The City University of New York, New York, NY 10016, U.S.A. Hunter College High School, New York, NY 10128, U.S.A., Department of Computer Science, Hunter College, The City University of New York, New York, NY 10065, U.S.A., Department of Biological Sciences, Hunter College, The City University of New York New York, NY 10065, U.S.A. and The Graduate Center, The City University of New York, New York, NY 10016, U.S.A.
authors.forename: Lei
authors.initials: L
authors.lastname: Xie
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D053263:Gene Regulatory Networks; D006801:Humans; D010363:Pattern Recognition, Automated; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry*; D016415:Sequence Alignment / Q000379:methods*; D012984:Software
chemical_list: D011506:Proteins