Characterizing basal-like triple negative breast cancer using gene expression analysis: A data mining approach
作者：
Highlights：
• Data mining algorithms are explored to classify BLBC Basal-like breast cancers.
• Several ensembles of classifiers and features are proposed and evaluated.
• Several genes are identified in association with BLBC breast cancer.
• Identification of gene signatures can lead to new pathways to develop BLBC treatments.
• Predictive models gained prediction accuracy from a feature selection ensemble.
摘要
•Data mining algorithms are explored to classify BLBC Basal-like breast cancers.•Several ensembles of classifiers and features are proposed and evaluated.•Several genes are identified in association with BLBC breast cancer.•Identification of gene signatures can lead to new pathways to develop BLBC treatments.•Predictive models gained prediction accuracy from a feature selection ensemble.
论文关键词：Gene expression,Basal-like breast cancer,Triple-negative breast cancer,Data mining
论文评审过程：Received 7 August 2019, Revised 24 November 2019, Accepted 29 January 2020, Available online 30 January 2020, Version of Record 6 February 2020.
论文官网地址：https://doi.org/10.1016/j.eswa.2020.113253
