Identifying Biomarkers Using Support Vector Machine to Understand the Racial Disparity in Triple-Negative Breast Cancer
Author:
Affiliation:
1. Department of Computer Science, Georgia State University, Atlanta, Georgia, USA.
2. Department of Biology and Marine Biology, University of North Carolina at Wilmington, Wilmington, North Carolina, USA.
Publisher
Mary Ann Liebert Inc
Subject
Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modeling and Simulation
Link
https://www.liebertpub.com/doi/pdf/10.1089/cmb.2022.0422
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1. Clinical significance of kallikrein-related peptidase (KLK10) mRNA expression in colorectal cancer
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3. The emerging roles of human tissue kallikreins in cancer
4. Knowledge-based analysis of microarray gene expression data by using support vector machines
5. Racial Disparities in Breast Cancer Diagnosis and Treatment by Hormone Receptor and HER2 Status
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1. Updated Biomarkers for TNBC in African vs. Caucasian American Women;2023-07-19
2. Deep Learning Reveals Biological Basis of Racial Disparities in Quadruple-Negative Breast Cancer;Bioinformatics Research and Applications;2023
3. Exploring Racial Disparities in Triple-Negative Breast Cancer: Insights from Feature Selection Algorithms;Bioinformatics Research and Applications;2023
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