Prediction and analysis of cell-penetrating peptides using pseudo-amino acid composition and random forest models

Amino Acids

Volumn 47, Issue 7, 2015, Pages 1485-1493

  Chen, Lei ^a,b   Chu, Chen ^c   Huang, Tao ^d   Kong, Xiangyin ^d   Cai, Yu Dong ^a  

^a SHANGHAI UNIVERSITY   (China)

^b SHANGHAI MARITIME UNIVERSITY   (China)

^c INSTITUTE OF BIOCHEMISTRY AND CELL BIOLOGY   (China)

^d Shanghai Jiao Tong University Affiliated Sixth People s Hospital   (China)

Author keywords

Cell penetrating peptide; Incremental feature selection; Minimum redundancy maximum relevance; Pseudo amino acid composition; Random forest

Indexed keywords

ASPARAGINE; ASPARTIC ACID; CELL PENETRATING PEPTIDE; GLUTAMIC ACID; GLUTAMINE; LYSINE; CODON;

ACCURACY; AMINO ACID COMPOSITION; ARTICLE; CALCULATION; CELL MEMBRANE; CODON; COMPARATIVE STUDY; MATHEMATICAL ANALYSIS; PH; PREDICTION; PRIORITY JOURNAL; PROTEIN SECONDARY STRUCTURE; RANDOM FOREST; AMINO ACID SEQUENCE; CHEMICAL MODEL; CHEMICAL STRUCTURE; CHEMISTRY; DECISION TREE;

AMINO ACID SEQUENCE; CELL-PENETRATING PEPTIDES; CODON; DECISION TREES; MODELS, CHEMICAL; MODELS, MOLECULAR; PROTEIN STRUCTURE, SECONDARY;

EID: 84930543023     PISSN: 09394451     EISSN: 14382199     Source Type: Journal    
DOI: 10.1007/s00726-015-1974-5     Document Type: Article

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