Predicting protein-binding RNA nucleotides using the feature-based removal of data redundancy and the interaction propensity of nucleotide triplets

Computers in Biology and Medicine

Volumn 43, Issue 11, 2013, Pages 1687-1697

  Choi, Sungwook ^a   Han, Kyungsook ^a  

^a Inha University   (South Korea)

Author keywords

Data redundancy removal; Interaction propensity; Protein binding nucleotide; Protein RNA interaction

Indexed keywords

CORRELATION COEFFICIENT; DATA REDUNDANCY; INTERACTION PROPENSITY; PROTEIN-BINDING; PROTEIN-BINDING SITES; PROTEIN-RNA INTERACTION; REDUNDANCY REMOVAL; SEQUENCE SIMILARITY;

AMINO ACIDS; BIOCHEMISTRY; FORECASTING; NUCLEOTIDES; PROTEINS; REDUNDANCY; SUPPORT VECTOR MACHINES;

RNA;

NUCLEOTIDE;

AMINO ACID SEQUENCE; ARTICLE; BINDING SITE; HYDROGEN BOND; KERNEL METHOD; MOLECULAR WEIGHT; PERFORMANCE; PREDICTION; PRIORITY JOURNAL; PROTEIN BINDING; PROTEIN DATA BANK; PROTEIN INTERACTION; PROTEIN RNA BINDING; RNA BINDING; RNA SEQUENCE; SUPPORT VECTOR MACHINE; X RAY CRYSTALLOGRAPHY;

DATA REDUNDANCY REMOVAL; INTERACTION PROPENSITY; PROTEIN-BINDING NUCLEOTIDE; PROTEIN-RNA INTERACTION;

AMINO ACID SEQUENCE; BINDING SITES; CODON; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; MODELS, MOLECULAR; MODELS, STATISTICAL; MOLECULAR SEQUENCE DATA; REPRODUCIBILITY OF RESULTS; RIBONUCLEOTIDES; RNA; RNA-BINDING PROTEINS; SUPPORT VECTOR MACHINES;

EID: 84884126060     PISSN: 00104825     EISSN: 18790534     Source Type: Journal    
DOI: 10.1016/j.compbiomed.2013.08.011     Document Type: Article

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