Advancements within Modern Machine Learning Methodology: Impacts and Prospects in Biomarker Discovery.

Journal: Current medicinal chemistry
Published Date:

Abstract

BACKGROUND: The adoption of biomarkers as part of high-throughput, complex microarray or sequencing data has necessitated the discovery and validation of these data through machine learning. Machine learning has remained a fundamental and indispensable tool due to its efficacy and efficiency in both feature extraction of relevant biomarkers as well as the classification of samples as validation of the discovered biomarkers.

Authors

  • Dakila Ledesma
    Department of Computer Science and Engineering, University of Tennessee at Chattanooga, Tennessee, TN 37996, United States.
  • Steven Symes
    Department of Chemistry and Physics, University of Tennessee at Chattanooga, 615 McCallie Ave., Chattanooga, TN, 37403, USA.
  • Sean Richards
    Department of Biology, Geology and Environmental Sciences, University of Tennessee at Chattanooga, 615 McCallie Ave., Chattanooga, TN, 37403, USA.