Google -owned AI specialist, DeepMind, has claimed a “significant milestone” in being able to demonstrate the usefulness of artificial intelligence to help with the complex task of predicting 3D structures of proteins based solely on their genetic sequence. Understanding protein structures is important in disease diagnosis and treatment, and could improve scientists’ understanding of the human body — as well as potentially helping to support protein design and bioengineering. Writing in a blog post about the project to use AI to predict how proteins fold — now two years in — it writes: “The 3D models of proteins that AlphaFold [DeepMind’s AI] generates are far more accurate than any that have come before — making significant progress on one of the core challenges in biology.” There are various scientific methods for predicting the native 3D state of protein molecules (i.e.
Deepmind Claims Early Progress In Ai-based Predictive Protein Modelling
Natasha Lomas, TechCrunch
Mon, 12/03/2018 - 3:51am
Topics: google owned ai understanding writing the 3d alphafold deepmind s ai dna there s foldit specifically fortunately alphafold casp community wide experiment critical assessment techniques protein structure prediction we re a7d we even ai deepmind the deepmind alphafold casp we our the early progress modelling structures methods acids learning amino neural writes data accurate distances commonly predictions predicting genetic problem network years properties proposed impact blog task complex separate making approaches folding demonstrate sequence improve scientific native state significant post human quantifiable biology approach fragments resulted team work pieces machine highly estimate method computational genomic advance score networks construct focused achieved
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