Selecting marker genes for cancer classification using supervised weighted kernel clustering and the support vector machine

DOI10.1016/j.csda.2008.04.028zbMath1453.62198OpenAlexW1975408252MaRDI QIDQ961343

Insuk Sohn, Jae Won Lee, Paul E. Green, Changha Hwang, Jooyong Shim, Sujong Kim

Publication date: 30 March 2010

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2008.04.028

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (4)

Transcription factor-binding site identification and gene classification via fusion of the supervised-weighted discrete kernel clustering and support vector machine ⋮ Bayesian classification for bivariate normal gene expression ⋮ Editorial: Statistical genetics \& statistical genomics: where biology, epistemology, statistics, and computation collide ⋮ Non-parametric detection of meaningless distances in high dimensional data

Uses Software

• LIBSVM
• Khan Academy
• boost

Cites Work

• Classification of gene functions using support vector machine for time-course gene expression data
• Comparison of Discrimination Methods for the Classification of Tumors Using Gene Expression Data
• Gene selection for cancer classification using support vector machines
• Unnamed Item

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