Machine Learning Enhances Drug Discovery Capabilities

GEN | October 23, 2019

Researchers at the Sanford Burnham Prebys Medical Discovery Institute say that machine learning’s powerful ability to detect patterns in complex data is revolutionizing how scientists diagnose disease and, now, how they discover new drugs. The Sanford Burnham team has developed a machine-learning algorithm that gleans information from microscope images that allow for high-throughput epigenetic drug screens. They believe that this approach (“Improving drug discovery using image-based multiparametric analysis of the epigenetic landscape”), described in eLife, could unlock new treatments for cancer, heart disease, mental illness, and other diseases. “High-content phenotypic screening has become the approach of choice for drug discovery due to its ability to extract drug-specific multi-layered data. In the field of epigenetics, such screening methods have suffered from a lack of tools sensitive to selective epigenetic perturbations. Here we describe a novel approach, Microscopic Imaging of Epigenetic Landscapes (MIEL), which captures the nuclear staining patterns of epigenetic marks and employs machine learning to accurately distinguish between such patterns,” the investigators wrote.

Spotlight

This video about biotechnology and its scope.

Spotlight

This video about biotechnology and its scope.

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Quantgene Demonstrates Game-Changing Sequencing Precision in GENES, A Leading Scientific Journal

Quantgene | June 08, 2021

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Amyris | October 23, 2020

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