De Novo Prediction of RNA 3D Structures with Deep Learning
Keyword(s):
De Novo
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We present a Deep Learning approach to predict 3D folding structures of RNAs from their nucleic acid sequence. Our approach combines an autoregressive Deep Generative Model, Monte Carlo Tree Search, and a Score Model to find and rank the most likely folding structures for a given RNA sequence. We confirm the predictive power of our approach by setting new benchmarks for some longer sequences in a simulated blind test of the RNA Puzzles prediction challenge.
2018 ◽
Vol 42
(4)
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pp. 1-5
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