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INTERPRETABLE MACHINE LEARNING

Mining for informative signals in biological sequences

Deep learning models for sequential data can be trained to make accurate predictions from large biological datasets. New tools from computer vision and natural language processing can help us make these models interpretable to biologists.

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Fig. 1: High-level architecture of the scrambler architecture.

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Correspondence to Ahmed M. Alaa.

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Alaa, A.M. Mining for informative signals in biological sequences. Nat Mach Intell (2022). https://doi.org/10.1038/s42256-022-00524-1

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  • DOI: https://doi.org/10.1038/s42256-022-00524-1

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