title: A genetic filter for cancer classification on gene expression data.
abstract: We present a new genetic filter to identify a predictive gene subset for cancer-type classification on gene expression profiles. This approach pursues to not only maximize correlation between selected genes and cancer types but also minimize inter-correlation among selected genes. The proposed genetic filter was tested on well-known leukemia datasets, and significant improvement over previous work was obtained.
authors.affiliation: Department of Computer Science & Engineering, Kwangwoon University, 20 Kwangwoon-ro, Nowon-gu, Seoul 139-701, Republic of Korea.
authors.forename: Yong-Hyuk
authors.initials: YH
authors.lastname: Kim
authors.affiliation: Department of Computer Engineering, College of Information Technology, Gachon University, 1342 Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do 461-701, Republic of Korea.
authors.forename: Yourim
authors.initials: Y
authors.lastname: Yoon
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D020869:Gene Expression Profiling; D015973:Gene Expression Regulation, Leukemic; D006801:Humans; D007938:Leukemia / Q000235:genetics*; D059467:Transcriptome
keywords: Gene selection; cancer classification; filter method; gene expression data; genetic algorithm