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 ...

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 ...

Google DeepMind, the artificial intelligence company behind the popular AlphaFold tool, has published the next generation of the application’s protein structure prediction software. The new tool can ...

Inside each cell of the human body are proteins that control which genes are expressed at the right place and time. However, intriguingly, many of the most important proteins involved in gene ...

The open-source AI model improves transparency in predicting how proteins interact with other molecules, which could speed up drug discovery.

Today (September 21), the Lasker Foundation announced this year’s award winners. John Jumper, a computational biologist at DeepMind, and Demis Hassabis, cofounder and CEO at DeepMind, were awarded 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, ...

Researchers recently published findings that could lay the groundwork for applying quantum computing methods to protein structure prediction. Researchers from Cleveland Clinic and IBM recently ...

Often referred to as the "powerhouses of the cell," mitochondria are well known for their role as energy suppliers, but these organelles are also critical for maintaining our overall health.

Ramachandran’s work helped explain the fundamental structure of proteins ... For these proteins to function, they must fold into precise shapes. Ramachandran developed the phi-psi plot, a diagram that ...