De Novo Prediction of RNA 3D Structures with Deep Learning
Ramakers, J.; Blum, C. F.; König, S.; Harmeling, S.; Kollmann, M.
Show abstract
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.
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