ConDo: protein domain boundary prediction using coevolutionary information.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Domain boundary prediction is one of the most important problems in the study of protein structure and function. Many sequence-based domain boundary prediction methods are either template-based or machine learning (ML) based. ML-based methods often perform poorly due to their use of only local (i.e. short-range) features. These conventional features such as sequence profiles, secondary structures and solvent accessibilities are typically restricted to be within 20 residues of the domain boundary candidate.

Authors

  • Seung Hwan Hong
    Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul, South Korea.
  • Keehyoung Joo
    Center for In Silico Protein Science, Korea Institute for Advanced Study, Seoul, South Korea.
  • Jooyoung Lee
    Center for In Silico Protein Science and School of Computational Sciences, Korea Institute for Advanced Study, Seoul 130-722, Korea.