Gene-expression-based cancer subtypes prediction through feature selection and transductive SVM

IEEE Transactions on Biomedical Engineering

Volumn 60, Issue 4, 2013, Pages 1111-1117

  Maulik, Ujjwal ^a   Mukhopadhyay, Anirban ^b   Chakraborty, Debasis ^c  

^a JADAVPUR UNIVERSITY   (India)

^b UNIVERSITY OF KALYANI   (India)

^c Murshidabad College of Engineering and Technology   (India)

Author keywords

Low density separation (LDS); microarray data; semisupervised classification; support vector machines (SVM); transductive learning

Indexed keywords

GENE EXPRESSION PROFILING; GREEDY SEARCH ALGORITHMS; LOW DENSITY; MICROARRAY DATA; MICROARRAY TECHNOLOGIES; SEMI-SUPERVISED CLASSIFICATION; TRANSDUCTIVE LEARNING; TRANSDUCTIVE SUPPORT VECTOR MACHINE;

DISEASES; FORECASTING; SUPPORT VECTOR MACHINES; TISSUE;

GENE EXPRESSION;

MIXED LINEAGE LEUKEMIA PROTEIN;

ALGORITHM; ARTICLE; CANCER CLASSIFICATION; CANCER DIAGNOSIS; FOLLOW UP; GENE EXPRESSION; LARGE CELL LYMPHOMA; LEUKEMIA; MARKER GENE; MICROARRAY ANALYSIS; SIGNAL NOISE RATIO; SUPPORT VECTOR MACHINE;

ALGORITHMS; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; GENE EXPRESSION PROFILING; GENETIC MARKERS; HUMANS; MODELS, BIOLOGICAL; NEOPLASMS; SIGNAL-TO-NOISE RATIO; SUPPORT VECTOR MACHINES; TUMOR MARKERS, BIOLOGICAL;

EID: 84875516745     PISSN: 00189294     EISSN: 15582531     Source Type: Journal    
DOI: 10.1109/TBME.2012.2225622     Document Type: Article

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