Discovering new in silico tools for antimicrobial peptide prediction

Current Drug Targets

Volumn 13, Issue 9, 2012, Pages 1148-1157

  Torrent, Marc ^a   Nogués, M Victòria ^a   Boix, Ester ^a  

^a UNIVERSITAT AUTÒNOMA DE BARCELONA   (Spain)

Author keywords

Antimicrobial peptides; Artificial neural networks; Database; Prediction; QSAR; Support vector machines

Indexed keywords

DEFENSIN; POLYPEPTIDE ANTIBIOTIC AGENT;

ACCURACY; AMINO ACID COMPOSITION; ARTIFICIAL NEURAL NETWORK; BACTERICIDAL ACTIVITY; BIOINFORMATICS; COMPUTER MODEL; CYTOTOXICITY; DATA BASE; DRUG DESIGN; HUMAN; MINIMUM INHIBITORY CONCENTRATION; NONHUMAN; PHYSICAL CHEMISTRY; PREDICTION; PROTEIN MOTIF; PSEUDOMONAS AERUGINOSA; QUANTITATIVE STRUCTURE ACTIVITY RELATION; REVIEW; SENSITIVITY AND SPECIFICITY; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS; SUPPORT VECTOR MACHINE; TRANSDUCER;

ANTI-INFECTIVE AGENTS; PEPTIDES; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 84864561211     PISSN: 13894501     EISSN: 18735592     Source Type: Journal    
DOI: 10.2174/138945012802002311     Document Type: Review

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