Multi-view feature selection for identifying gene markers: a diversified biological data driven approach

Multi-view feature selection for identifying gene markers: a diversified biological data driven approach

Abstract Background In recent years, to investigate challenging bioinformatics problems, the utilization of multiple genomic and proteomic sources has become immensely popular among researchers. One such issue is feature or gene selection and identifying relevant and non-redundant marker genes from...

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Bibliographic Details
Main Authors: Sudipta Acharya, Laizhong Cui, Yi Pan
Format: Article
Language:English
Published: BMC 2020-12-01
Series:BMC Bioinformatics
Subjects:
Gene selection
Sample classification
Gene ontology (GO)
Protein–protein interaction network (PPIN)
Multi-view learning
Multi-objective clustering
Online Access:https://doi.org/10.1186/s12859-020-03810-0

Internet

https://doi.org/10.1186/s12859-020-03810-0

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