MGRFE: Multilayer Recursive Feature Elimination Based on an Embedded Genetic Algorithm for Cancer Classification

Microarray gene expression data have become a topic of great interest for cancer classification and for further research in the field of bioinformatics. Nonetheless, due to the "large <inline-formula><tex-math notation="LaTeX">p</tex-math> <mml:math><mml:mi&...

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Veröffentlicht in:	IEEE/ACM transactions on computational biology and bioinformatics Jg. 18; H. 2; S. 621 - 632
Hauptverfasser:	Peng, Cheng, Wu, Xinyu, Yuan, Wen, Zhang, Xinran, Zhang, Yu, Li, Ying
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.03.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Bioinformatics Cancer cancer classification Classification Computational Biology - methods Databases, Genetic Datasets DNA microarrays Feature extraction Feature selection Gene expression Gene Expression Profiling Gene selection Genes genetic algorithm Genetic algorithms Heuristic algorithms Humans microarray data Microwave integrated circuits Models, Genetic Multilayers Neoplasms - classification Neoplasms - genetics Neoplasms - metabolism Nonhomogeneous media Oligonucleotide Array Sequence Analysis Phenotypes Polynomials recursive feature elimination Source code Transcriptome - genetics
ISSN:	1545-5963, 1557-9964, 1557-9964
Online-Zugang:	Volltext
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