GeneDisco: A Benchmark for Experimental Design in Drug Discovery

Published in ICLR, 2022

Recommended citation: Mehrjou A, Soleymani A, Jesson A, Notin P, Gal Y, Bauer S, Schwab P. GeneDisco: A Benchmark for Experimental Design in Drug Discovery. arXiv preprint arXiv:2110.11875. 2021 Oct 22.

We introduce GeneDisco, an open benchmark suite for batch active learning for drug discovery that provides curated datasets, tasks, performance evaluation and open source implementations of state-of-the-art algorithms for experimental exploration.

  • We perform an extensive experimental baseline evaluation that establishes the relative performance of existing state-of-the-art methods on all the developed benchmark settings using a total of more than 20 000 central processing unit (CPU) hours of compute time.
  • We survey and analyse the current state-of-the-art of active learning for biological exploration in the context of the generated experimental results, and present avenues of heightened potential for future research based on the developed benchmark.


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