• DocumentCode
    573711
  • Title

    Predicting protein-RNA residue-base contacts using two-dimensional conditional random field

  • Author

    Hayashida, Morihiro ; Kamada, Mayumi ; Song, Jiangning ; Akutsu, Tatsuya

  • Author_Institution
    Bioinf. Center, Kyoto Univ., Kyoto, Japan
  • fYear
    2012
  • fDate
    18-20 Aug. 2012
  • Firstpage
    152
  • Lastpage
    157
  • Abstract
    Understanding of interactions between proteins and RNAs is essential to reveal networks and functions of molecules in cellular systems. Many studies have been done for analyzing and investigating interactions between protein residues and RNA bases. For interactions between protein residues, it is supported that residues at interacting sites have co-evolved with the corresponding residues in the partner protein to keep the interactions between the proteins. In our previous work, on the basis of this idea, we calculated mutual information (MI) between residues from multiple sequence alignments of homologous proteins for identifying interacting pairs of residues in interacting proteins, and combined it with the discriminative random field (DRF), which is useful to extract some characteristic regions from an image in the field of image processing, and is a special type of conditional random fields (CRFs). In a similar way, in this paper, we make use of mutual information for predicting interactions between protein residues and RNA bases. Furthermore, we introduce labels of amino acids and bases as features of a simple two-dimensional CRF instead of DRF. To evaluate our method, we perform computational experiments for several interactions between Pfam domains and Rfam entries. The results suggest that the CRF model with MI and labels is more useful than the CRF model with only MI.
  • Keywords
    RNA; bioinformatics; cellular biophysics; learning (artificial intelligence); molecular biophysics; proteins; statistical analysis; 2D CRF; 2D conditional random field; DRF; RNA bases; amino acid labels; biomolecular functions; biomolecular networks; cellular systems; conditional random fields; discriminative random field; homologous proteins; multiple sequence alignments; mutual information; protein residue interactions; protein residues; protein-RNA interactions; protein-RNA residue base contact prediction; Amino acids; Computational modeling; Mutual information; Protein sequence; RNA; Random variables;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems Biology (ISB), 2012 IEEE 6th International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    978-1-4673-4396-1
  • Electronic_ISBN
    978-1-4673-4397-8
  • Type

    conf

  • DOI
    10.1109/ISB.2012.6314128
  • Filename
    6314128