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
Link To Document