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Huang et al., 2018 - Google Patents

Applications of support vector machine (SVM) learning in cancer genomics

Huang et al., 2018

View PDF @Free from Publisher
Document ID
17360140635904123979
Author
Huang S
Cai N
Pacheco P
Narrandes S
Wang Y
Xu W
Publication year
Publication venue
Cancer genomics & proteomics

External Links

Snippet

Machine learning with maximization (support) of separating margin (vector), called support vector machine (SVM) learning, is a powerful classification tool that has been used for cancer genomic classification or subtyping. Today, as advancements in high-throughput …
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Classifications

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    • G06F19/24—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for machine learning, data mining or biostatistics, e.g. pattern finding, knowledge discovery, rule extraction, correlation, clustering or classification
    • G—PHYSICS
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    • G06F19/18—Bioinformatics, i.e. methods or systems for genetic or protein-related data processing in computational molecular biology for functional genomics or proteomics, e.g. genotype-phenotype associations, linkage disequilibrium, population genetics, binding site identification, mutagenesis, genotyping or genome annotation, protein-protein interactions or protein-nucleic acid interactions
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