sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and <i>t</i> Statistic.

Das, Pijush; Roychowdhury, Anirban; Das, Subhadeep; Roychoudhury, Susanta; Tripathy, Sucheta

sigFeature: Novel Significant Feature Selection Method for Classification of Gene Expression Data Using Support Vector Machine and t Statistic.

Das, Pijush; Roychowdhury, Anirban; Das, Subhadeep; Roychoudhury, Susanta; Tripathy, Sucheta.

Afiliación

Das P; Computational Genomics lab, Structural Biology and Bioinformatics Division, CSIR- Indian Institute of Chemical Biology, Kolkata, India.
Roychowdhury A; Department of Oncogene Regulation, Chittaranjan National Cancer Institute, Kolkata, India.
Das S; Computational Genomics lab, Structural Biology and Bioinformatics Division, CSIR- Indian Institute of Chemical Biology, Kolkata, India.
Roychoudhury S; Saroj Gupta Cancer Centre and Research Institute, Kolkata, India.
Tripathy S; Computational Genomics lab, Structural Biology and Bioinformatics Division, CSIR- Indian Institute of Chemical Biology, Kolkata, India.

Front Genet ; 11: 247, 2020.

Article en En | MEDLINE | ID: mdl-32346383

Palabras clave

GSEA; RNA-Seq; bootstrap; cancer; feature selection; machine learning; microaaray; support vector machine

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Texto completo: 1 Banco de datos: MEDLINE Tipo de estudio: Prognostic_studies Idioma: En Revista: Front Genet Año: 2020 Tipo del documento: Article País de afiliación: India

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