GENERALIZED COMPUTATIONAL FRAMEWORK AND SYSTEM FOR INTEGRATIVE PREDICTION OF BIOMARKERS
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Jan 11, 2024
app pub date -
Sep 26, 2023
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Dec 12, 2016
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Abstract
An approach is provided to computationally identify biomarkers associated with diseases and medical conditions. The procedure first identifies biomarkers individually at the DNA, RNA and proteome levels. Then provides a methodology to integrate the single-source biomarkers and perform dimensionality reduction in order to detect the most informative subset of biomarkers that better distinguish samples between two biological conditions (disease vs normal samples). The dimensionality reduction step minimizing biases due to unnecessary or partially correlated biomarkers and significantly reduces the search space of possible biomarkers. An algorithm is also described for the automated optimization of the proposed DNA-seq and RNA-seq pipelines.
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