This review provides an overview of traditional and modern methods for protein structure prediction and their characteristics and introduces the groundbreaking network features of the AlphaFold family ...

Researchers from Cleveland Clinic and IBM recently published findings in the Journal of Chemical Theory and Computation that could lay the groundwork for applying quantum computing methods to protein ...

In the rapidly advancing field of computational biology, a newly peer-reviewed review explores the transformative role of deep learning techniques in revolutionizing protein structure prediction. The ...

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 engineering is a powerful biotechnological process that focuses on creating new enzymes or proteins and improving the functions of existing ones by manipulating their natural macromolecular ...

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 ...

The “ChatGPT moment” for biology proceeds to unfold as protein language models, or machine learning tools trained on large databases of protein sequences, work to decode the language of life with the ...

In the wee hours of an October morning, David Baker, a protein biologist at the University of Washington (UW), received the most-awaited phone call in a scientist’s career. Halfway around the world, ...

In the rapidly advancing field of computational biology, a review explores the transformative role of deep learning techniques in revolutionizing protein structure prediction. The review, published in ...