Characterization of novel HIV drug resistance mutations using clustering, multidimensional scaling and SVM-based feature ranking

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3721 LNAI, Issue , 2005, Pages 285-296

  Sing, Tobias ^a   Svicher, Valentina ^b   Beerenwinkel, Niko ^c   Ceccherini Silberstein, Francesca ^b   Däumer, Martin ^d   Kaiser, Rolf ^d   Walter, Hauke ^e   Korn, Klaus ^e   Hoffmann, Daniel ^f   Oette, Mark ^g   Rockstroh, Jürgen K ^h   Fätkenheuer, Gert ^d   Perno, Carlo Federico ^b   Lengauer, Thomas ^a  

^a MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

^b UNIVERSITY OF ROME TOR VERGATA   (Italy)

^c UNIVERSITY OF CALIFORNIA   (United States)

^d UNIVERSITY OF COLOGNE   (Germany)

^e UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

^f CENTER OF ADVANCED EUROPEAN STUDIES AND RESEARCH CAESAR   (Germany)

^g HEINRICH HEINE UNIVERSITY   (Germany)

^h UNIVERSITY OF BONN   (Germany)

Author keywords

Clustering; Feature ranking; HIV; Multidimensional scaling; Support vector machines

Indexed keywords

DATA MINING; DATABASE SYSTEMS; GENES; HIERARCHICAL SYSTEMS;

FEATURE RANKING; MULTIDIMENSIONAL SCALING; MUTATIONS; SUPPORT VECTOR MACHINES;

DRUG THERAPY;

EID: 33646418385     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11564126_30     Document Type: Conference Paper

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