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  "documentTitle": "2021 Air Street Capital The State of AI Report 2021",
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      "text": "In the RNA-Puzzles challenge, ARES selects the best Rosetta FARFAR2 model for each of four RNA molecules, beating humans and other methods, despite significant differences with its training set.",
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      "text": "Visual comparison of ARES prediction vs best competing prediction against crystal structure.",
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      "text": "A new method called Atomic Rotationally Equivariant Scorer (ARES) processes the 3D coordinates and chemical element type of each atom of an RNA molecule and predicts the root mean square deviation (RMSD) from the unknown true structure.\nARES is trained on 18 RNA molecules with experimentally determined structures and 1,000 structural models of these RNAs sampled with Rosetta's FARFAR2. ARES is optimised such that its output is as close to the RMSD of the models as possible.\nNotably, ARES isn't given any prior information about what RNA molecules are, nor does it use sequences of related RNAs.\nIn the RNA-Puzzles challenge, ARES selects the best Rosetta FARFAR2 model for each of four RNA molecules, beating humans and other methods, despite significant differences with its training set.",
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      "text": "RMSD (Å): 4.8",
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      "text": "Single-stranded RNAs (e.g mRNAs) fold into well-defined 3D structures to effect their biological function. Unlike proteins, we know little about RNA folding and the number of available RNA structures is 1% of that for proteins.",
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