Our scientists have developed a set of chemical benchmarks to better understand exactly what our computational models are learning. At Atomwise, AtomNet® structure-based models can quickly identify active compounds for protein targets from large […]
Atomwise scientists are adapting machine learning models to make predictions about a class of drug compounds that has been challenging to study.
Our researchers are developing an automated pipeline that can more accurately identify promising compounds targeting multi-site proteins
With the implementation of genomic technologies, medicine is becoming increasingly personalized thanks to new treatments that target important molecular targets. In the context of Parkinson's disease, there is an urgent need to identify molecular […]
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