New protein-folding AI vastly expands on Alphafold's efforts
The new open-source atlas, generated by an AI tool called ESMFold2, vastly increases the known protein universe
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The new open-source atlas, generated by an AI tool called ESMFold2, vastly increases the known protein universe
A new approach guides AlphaFold with experimental data, helping it predict flexible protein shape ensembles instead of single static structures.
Google DeepMindで「AlphaFold」の開発を主導し、デミス・ハサビスCEOと共にノーベル化学賞を受賞したジョン・ジャンパー氏が、Anthropicに移ると自身のXで明らかにした。直近では「Gemini」を...
In a preprint published in arXiv, researchers from Altos Labs have described a machine learning algorithm that performs end-to-end prediction of how cells’ gene expression will res...
Deep Principle released MPA (Materials Property Axiom), an AI foundation model for materials science that achieves state-of-the-art results on 40 real-world industrial tasks by bor...
by Adam Wu, Jakub Lála, Quentin Trolliet, Abhinav Rajendran, Stefano Angioletti-Uberti We present a hybrid approach combining a protein language model (pLM) with Monte Carlo (MC)...
by Lijuan Wang, Yuze Wang, Chen Qiu, Liwei Xiao, Xianliang Liu, Junjie Chen Protein sequence design for tailored functional properties is a fundamental task in protein engineering...
Computational chemistry researchers have traditionally faced a frustrating trade-off when simulating molecular interactions: use fast classical force fields that sacrifice precisio...
John Jumper / @johnjumpersci: John Jumper, who won the Nobel Prize “for protein structure prediction”, says he is leaving Google DeepMind after nearly nine years to join Anthropic ...
by Weihe Dong, Qiang Yang, Long Xu, Xiaokun Li, Kuanquan Wang, Suyu Dong, Gongning Luo, Xianyu Zhang, Tiansong Yang, Xin Gao, Guohua Wang Deciphering how human T cells recognise p...
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