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 ...
The latest update to the ESM protein language model series supports binder design and protein function mapping for therapeutic discovery.
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 ...
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 ...
In a study published in Nature Methods, a research group developed a highly sensitive proteomics method called peptide-centric local stability assay (PELSA), which enables the simultaneous ...
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.
Researchers studying the dark proteome are investigating proteins that lack clear structures or known functions. Experts, ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results