SVMTriP: A Method to Predict Antigenic Epitopes Using Support Vector Machine to Integrate Tri-Peptide Similarity and Propensity

PLoS ONE

Volumn 7, Issue 9, 2012, Pages

  Yao, Bo ^a   Zhang, Lin ^b   Liang, Shide ^c   Zhang, Chi ^a  

^a UNIVERSITY OF NEBRASKA   (United States)

^b UNIVERSITY OF NEBRASKA LINCOLN   (United States)

^c OSAKA UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

EPITOPE; TRIPEPTIDE;

ACCESS TO INFORMATION; ACCURACY; AMINO ACID SEQUENCE; AREA UNDER THE CURVE; ARTICLE; CLIENT SERVER APPLICATION; INTERNET; MATHEMATICAL ANALYSIS; PEPTIDE ANALYSIS; PREDICTION; PROPENSITY SCORE; SENSITIVITY AND SPECIFICITY; SEQUENCE HOMOLOGY; SUPPORT VECTOR MACHINE;

AMINO ACID SEQUENCE; ANIMALS; ANTIGENS; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; EPITOPE MAPPING; EPITOPES, B-LYMPHOCYTE; HUMANS; INTERNET; MOLECULAR SEQUENCE DATA; OLIGOPEPTIDES; REPRODUCIBILITY OF RESULTS; SUPPORT VECTOR MACHINES; VIRAL PROTEINS;

EID: 84866324402     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0045152     Document Type: Article

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