Adaptive compressive learning for prediction of protein-protein interactions from primary sequence

Journal of Theoretical Biology

Volumn 283, Issue 1, 2011, Pages 44-52

  Zhang, Ya Nan ^a   Pan, Xiao Yong ^a   Huang, Yan ^b   Shen, Hong Bin ^a  

^a BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

^b SHANGHAI INSTITUTE OF TECHNICAL PHYSICS   (China)

Author keywords

Compressed sensing; Nyquist sampling; Protein protein interactions prediction; Sequential discrete representation

Indexed keywords

ALGORITHM; BIOLOGICAL ANALYSIS; EXPERIMENTAL STUDY; GENETIC ANALYSIS; PROTEIN; SAMPLING; THEORETICAL STUDY; YEAST;

ACCURACY; ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; COMPRESSED SENSING THEORY; CONTROLLED STUDY; DATA ANALYSIS; NONHUMAN; PREDICTION; PRIORITY JOURNAL; PROTEIN PROTEIN INTERACTION; REDUNDANCY ANALYSIS; SACCHAROMYCES CEREVISIAE; SENSITIVITY AND SPECIFICITY; SEQUENCE ANALYSIS; SIGNAL PROCESSING; STATISTICAL ANALYSIS;

ALGORITHMS; AMINO ACID SEQUENCE; ARTIFICIAL INTELLIGENCE; CHEMISTRY, PHYSICAL; COMPUTATIONAL BIOLOGY; PROTEIN BINDING; PROTEIN INTERACTION MAPPING; SACCHAROMYCES CEREVISIAE; SACCHAROMYCES CEREVISIAE PROTEINS; SPECIES SPECIFICITY;

SACCHAROMYCES CEREVISIAE;

EID: 79958028560     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2011.05.023     Document Type: Article

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