In a recent study published in the journal Nature Machine Intelligence, researchers developed "DeepGO-SE," a method to predict gene ontology (GO) functions from protein sequences using a large, ...
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 ...
In an ambitious collaboration, researchers added 1.8 million high-confidence protein complex structure predictions to the AlphaFold Database, accelerating molecular biology research.
The 2024 Nobel Prize in Chemistry is for computational protein design and structure prediction. David Baker, Demis Hassabis and John M. Jumper took home the prize for their work using artificial ...
A new artificial intelligence model can predict how different proteins may bind to DNA. A new artificial intelligence model developed by USC researchers and published in Nature Methods can predict how ...
DNA sequence features predict genome-wide binding pattern of key protein involved in brain disorders
Researchers from the University of Illinois at Urbana-Champaign and the University of California-Davis (UC Davis) are combining in vivo experimentation with computation for highly accurate prediction ...
Proteins are important molecules that perform a variety of functions essential to life. To function properly, many proteins must fold into specific structures. However, the way proteins fold into ...
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AI model predicts peptide sequences that prevent ribosome stalling in E. coli protein production
Proteins sourced from microorganisms are attracting attention for their potential in biomanufacturing a variety of products, including pharmaceuticals, industrial enzymes, and diagnostic antibodies.
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