• DocumentCode
    3673178
  • Title

    A complexity measurement for de novo protein folding

  • Author

    Michael Scott Brown;James A. Coker;Olivia Minh Trang Hua

  • Author_Institution
    The Graduate School, ITS Department, University of Maryland, University College, Adelphi, MD, USA
  • fYear
    2015
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Predicting how a protein folds based solely on its amino acid sequence is an ongoing challenge for the fields of Bioinformatics and Computer Science. Previous attempts to solve this problem have relied on algorithms and a specific set of benchmark proteins. However, there is currently no method for determining if the set of benchmark proteins share a similar level of complexity with proteins of similar size. As a result, a larger variety of benchmarks might be needed to evade this problem and a measure of complexity established to determine the validity of all benchmarks. We propose here the Ouroboros Complexity Measurement for the de novo folding of proteins. This measurement is easy to compute (not an NP hard problem) and allows the comparing of protein complexity.
  • Keywords
    "Proteins","Complexity theory","Benchmark testing","Amino acids","Mathematical model","Software measurement","Nuclear magnetic resonance"
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence in Bioinformatics and Computational Biology (CIBCB), 2015 IEEE Conference on
  • Type

    conf

  • DOI
    10.1109/CIBCB.2015.7300282
  • Filename
    7300282