EternaBrain: Automated RNA design through move sets from an Internet-scale RNA videogame

bioRxiv(2019)

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摘要
Folded RNA molecules underlie emerging approaches to disease detection and gene therapy. These applications require RNA sequences that fold into target base-pairing patterns, but computational algorithms generally remain inadequate for these RNA secondary structure design tasks. The Eterna project has collected over 1 million player moves by crowdsourcing RNA designs in the form of puzzles that reach extraordinary difficulty. Here, we present these data in the eternamoves repository and test their utility in training a multilayer convolutional neural network to predict moves. When pipelined with hand-coded move combinations developed by the Eterna community, the resulting EternaBrain method solves 61 out of 100 independent RNA design puzzles in the Eterna100 benchmark. EternaBrain surpasses all six other prior algorithms that were not informed by Eterna strategies and suggests a path for automated RNA design to achieve human-competitive performance. The authors are grateful for pre-publication review; please use https://goo.gl/kXNzsb.
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关键词
Deep learning,artificial intelligence,RNA design,secondary structure
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