This fully updated volume explores a wide array of new and state-of-the-art tools and resources for protein function prediction. Beginning with in-depth overviews of essential underlying computational ...
Protein function prediction and annotation represent critical challenges in the post‐genomic era. As high‐throughput sequencing continues to generate vast amounts of protein data, computational ...
An international team led by Einstein Professor Cecilia Clementi in the Department of Physics at Freie Universität Berlin has introduced CGSchNet, a machine-learned coarse-grained (CG) model that can ...
Morning Overview on MSN
Protein-design AI has become a black box even its creators can't read — and scientists just laid out a plan to force it to show its work
The AI systems designing new proteins are getting remarkably good at their jobs. They generate novel molecular structures ...
Northwestern Medicine scientists have developed a new experimental method to analyze conformational fluctuations in protein ...
The Rocklin Lab at Northwestern University today announced the release of the MGnify Stability Dataset, a large-scale experimental resource containing folding stability measurements for 1.8 million ...
Researchers developed DeepAFM, an AI-based method that removes noise from protein imaging data and accurately identifies ...
CMS College researchers developed SPHAK, a model predicting cross-species virus transmission with over 97% accuracy using viral protein analysis.
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