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 ...

Recent advances in high-throughput proteomics enable the measurement of thousands of proteins simultaneously, offering ...

A newly developed generative AI model is helping researchers explore protein dynamics with increased speed. The deep learning system, called BioEmu, predicts the full range of conformations a protein ...

Researchers present BioEmu – a new AI model that rapidly and accurately predicts the full range of shapes a protein can adopt, offering a faster, cheaper alternative to traditional molecular ...

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 ...

OpenProtein.AI is helping biologists stay on the cutting edge of AI with a no-code platform for protein engineering.

Scientists at St. Jude Children's Research Hospital have created a database that provides updated predicted structures on a regular basis, ensuring scientists can work with the most current ...

Researchers have taken a significant step forward in understanding the stability of proteins by leveraging the power of AI. The research team used AlphaFold2 to explore how mutations affect protein ...

Proteomics is the large-scale study of proteins, particularly their structures and functions. It involves the systematic identification, quantification, and analysis of the entire protein complement ...

Researchers developed a method to evaluate the reliability of AI language models used in biology. The breakthrough offers a ...