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 ...
Announcing a new publication for Acta Materia Medica journal. Proteins are essential macromolecules that perform functions according to their conformational dynamics. Studying the conformational ...
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 ...
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 ...
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 ...
Baker, Hassabis, Jumper Awarded Nobel Prize in Chemistry for Protein Design and Structure Prediction
Three scientists were named winners of the 2024 Nobel Prize in Chemistry for their innovations in the fields of computational protein design and structure prediction. One half of the prize was awarded ...
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 ...
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.
Some results have been hidden because they may be inaccessible to you
Show inaccessible results