ECFS-DEA: an ensemble classifier-based feature selection for differential expression analysis on expression profiles

Background Various methods for differential expression analysis have been widely used to identify features which best distinguish between different categories of samples. Multiple hypothesis testing may leave out explanatory features, each of which may be composed of individually insignificant varia...

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Vydáno v:	BMC bioinformatics Ročník 21; číslo 1; s. 43 - 14
Hlavní autoři:	Zhao, Xudong, Jiao, Qing, Li, Hangyu, Wu, Yiming, Wang, Hanxu, Huang, Shan, Wang, Guohua
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London BioMed Central 05.02.2020 BioMed Central Ltd Springer Nature B.V BMC
Témata:	Accumulation Algorithms Analysis Bioinformatics Biomedical and Life Sciences Classification Classifiers Cluster analysis Clustering Computational Biology/Bioinformatics Computer Appl. in Life Sciences Computer simulation Differential expression analysis Discriminant analysis Expression profiles Feature selection Gene expression Gene Expression Profiling - methods Graphical user interface Hypotheses Life Sciences Linux Machine Learning and Artificial Intelligence in Bioinformatics Microarrays Personal computers Proteins ROC Curve Scattering theory Software Support vector machines Variables Vector quantization Work stations Taiwan Feature selection Expression profiles Differential expression analysis Accumulation Classification
ISSN:	1471-2105, 1471-2105
On-line přístup:	Získat plný text
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