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COMPUTATIONAL BIOLOGY

Automated sequence-based annotation and interpretation of the human genome

A machine-learning model produces summarized sequence representations of genomic regulatory activity, and provides a functional view of regulatory DNA variation in the human genome, with the aim of better understanding the role of sequence variation in health and disease.

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Fig. 1: Conceptual overview of the Sei framework.

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Correspondence to Anshul Kundaje or Wouter Meuleman.

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Competing interests

A.K. is scientific co-founder of Ravel Biotechnology, is on the scientific advisory board of PatchBio, SerImmune, AINovo, TensorBio and OpenTargets, is a consultant with Illumina and owns shares in DeepGenomics, Immuni and Freenome. W.M. has no competing interests.

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Kundaje, A., Meuleman, W. Automated sequence-based annotation and interpretation of the human genome. Nat Genet 54, 916–917 (2022). https://doi.org/10.1038/s41588-022-01123-x

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