Analysis and Prediction of Highly Effective Antiviral Peptides Based on Random Forests

PLoS ONE

Volumn 8, Issue 8, 2013, Pages

  Chang, Kuan Y ^a   Yang, Je Ruei ^a  

^a NATIONAL TAIWAN OCEAN UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

ANTIVIRUS AGENT; LYSINE; PROTEOME; VIRUS PROTEIN;

ALPHA HELIX; AMINO ACID COMPOSITION; ARTICLE; CONTROLLED STUDY; CORRELATION COEFFICIENT; DRUG IDENTIFICATION; DRUG STABILITY; DRUG STRUCTURE; HYDROPHOBICITY; MEASUREMENT ACCURACY; PHYSICAL CHEMISTRY; PREDICTION; PROTEIN AGGREGATION; PROTEIN SECONDARY STRUCTURE; RANDOM FOREST; STRUCTURE ANALYSIS;

ALGORITHMS; AMINO ACIDS; ANTIVIRAL AGENTS; MODELS, THEORETICAL; PEPTIDES; PROTEOMICS;

EID: 84881118027     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0070166     Document Type: Article

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