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LISA: Towards Learned DNA Sequence Search #1015
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Although not strictly deep learning, this paper presents an interesting application of machine learning to improve running time of DNA sequence search algorithms. I think this is interesting, because algorithms and data structures are important components of bioinformatics research but they have not really seen significant applications of ML yet. This paper, which is inspired by The Case for Learned Index Structures , signifies a change in that regard. Along with the Sapling paper, this is a sort of first application of ML to this aspect of bioinformatics. It is possible that we will continue to see similar works. As such, the review might benefit from us carefully speculating about whether deep learning might similarly benefit these fields, or whether deep learning is outperformed by ML here. It is entirely possible that deep learning is a poor fit here due to running time constraints, and that might be worth noting. |
https://arxiv.org/abs/1910.04728
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