Article

APNet, an explainable sparse deep learning model to discover differentially active drivers of severe COVID-19

2024-01-11

Abstract excerpt

<h4>Motivation</h4> Computational analyses of plasma proteomics provide translational insights into complex diseases such as COVID-19 by revealing molecules, cellular phenotypes, and signaling patterns that contribute to unfavorable clinical outcomes. Current in silico approaches dovetail differential expression, biostatistics, and machine learning, but often overlook nonlinear proteomic dynamics, like post-tran...

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Literature Corpus work: 3622a2ea-84df-5fff-acc9-4a7b02cde45a
DOI: 10.1101/2024.01.11.575161

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