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COMPUTATIONAL GENOMICS

Neural network architecture search with AMBER

Nature Machine Intelligence volume 3, pages 372–373 (2021)Cite this article

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Deep learning applied to genomics can learn patterns in biological sequences, but designing such models requires expertise and effort. Recent work demonstrates the efficiency of a neural network architecture search algorithm in optimizing genomic models.

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Fig. 1: Neural architecture search for genomic problems.

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Authors and Affiliations

  1. Department of Data Science, Dana-Farber Cancer Institute, Harvard T. H. Chan School of Public Health, Boston, MA, USA

    Yi Zhang, Yang Liu & X. Shirley Liu

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  1. Yi Zhang
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  2. Yang Liu
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  3. X. Shirley Liu
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Corresponding author

Correspondence to X. Shirley Liu.

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Competing interests

X.S.L. is a cofounder, board member, SAB, and consultant of GV20 Oncotherapy and its subsidiaries, SAB of 3DMedCare, consultant for Genentech, and stockholder of AMGN, JNJ, MRK, PFE, and receives sponsored research funding from Takeda and Sanofi.

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Zhang, Y., Liu, Y. & Liu, X.S. Neural network architecture search with AMBER. Nat Mach Intell 3, 372–373 (2021). https://doi.org/10.1038/s42256-021-00350-x

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