What is it about?
Fibrosis contributes to most chronic diseases, including heart disease, diabetes, and cancer. There is a great need to discover and understand drugs against fibrosis. Here, we combine machine learning with a computer model that integrates prior human knowledge to identify how several drugs work.
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Photo by Myriam Zilles on Unsplash
Why is it important?
This study illustrates how machine learning and human learning can be fruitfully combined, benefitting from the predictive power of algorithms with the explanatory strengths of prior mechanistic experiments.
Perspectives
We have been developing mechanistic computer models of cells for several years, and separately we've been using machine learning for data analysis. I'm excited by how this combined logic-based mechanistic machine learning approach overcomes a previous barrier of modeling the pathways that regulate novel cell features.
Jeff Saucerman
University of Virginia
Read the Original
This page is a summary of: Logic-based mechanistic machine learning on high-content images reveals how drugs differentially regulate cardiac fibroblasts, Proceedings of the National Academy of Sciences, January 2024, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2303513121.
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