Large-Scale Automatic Feature Selection for Biomarker Discovery in High-Dimensional OMICs Data

Volume: 10
Published: May 16, 2019
Abstract
The identification of biomarker signatures in omics molecular profiling is usually performed to predict outcomes in a precision medicine context, such as patient disease susceptibility, diagnosis, prognosis, and treatment response. To identify these signatures, we have developed a biomarker discovery tool, called BioDiscML. From a collection of samples and their associated characteristics, i.e., the biomarkers (e.g., gene expression, protein...
Paper Details
Title
Large-Scale Automatic Feature Selection for Biomarker Discovery in High-Dimensional OMICs Data
Published Date
May 16, 2019
Volume
10
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