Recent advances in computational biology have revolutionised the field of protein structure and function prediction. Traditionally, determining the three‐dimensional architecture of a protein from its ...

With MassiveFold, scientists have unlocked AlphaFold's full potential, making high-confidence protein predictions faster and more accessible, fueling breakthroughs in biology and drug discovery. Brief ...

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 ...

In 2020, news headlines repeated John Moult’s words at the end of a stunning competition: Artificial intelligence had “solved” a long-standing grand challenge in biology, protein structure prediction.

Fully open source model accurately predicts the 3D structures of proteins and biomolecules in silico, and serves as a foundational model for next generation of cutting-edge Protein AI tools The ...

Neo-1 is the first model to unify de novo molecular generation and atomic-level structure prediction in a single model, by generating latent representations of whole molecules instead of predicting ...

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 ...

Genesis’ proprietary foundation model – Pearl – outperforms frontier models, including AlphaFold 3, on key benchmarks that predict utility in real-world drug discovery Pearl’s performance improved ...

Google DeepMind’s work with AlphaFold has been nothing short of a miracle, but it is computationally expensive. With that in mind, Apple researchers set off to develop an alternative method to use AI ...