# Enformer and Borzoi (DeepMind, Calico)

Source: https://onco.cc/technologies/enformer-borzoi/  
OnCo record `enformer-borzoi` (Technology). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

Models that predict how DNA sequence controls gene activity, used to interpret non-coding cancer mutations.

## Summary

Enformer and Borzoi are sequence-to-function models that predict how DNA controls gene activity by combining convolution with a transformer over long DNA windows. Enformer (Nature Methods 2021, DeepMind) predicts gene expression and chromatin signals from 200 kb of sequence; Borzoi (Nature Genetics 2025, Calico) extends this to predicting RNA-seq coverage and splicing across 500 kb. Both are used to interpret non-coding variants, including candidate cancer drivers in promoters and enhancers, by comparing predictions for reference and mutant sequence. Their cell-type coverage is bounded by the assays in the training data, so effects in tissues or tumour states that were never profiled cannot be predicted reliably. For a newcomer: these models read a long stretch of DNA and predict how a mutation there would change which genes are switched on.

## Fields

- Kind: Technology
- Status: emerging
- Last checked: 2026-09-08
- Tags: foundation-model; genome
- Principle: Enformer and Borzoi combine convolution with a transformer over long DNA windows.
- Since: 2021
- Strengths: Regulatory variant interpretation
- Limitations: Cell-type coverage bounded by training assays

## Sources

- Enformer, Nature Methods 2021: https://doi.org/10.1038/s41592-021-01252-x
- Borzoi, Nature Genetics 2025: https://doi.org/10.1038/s41588-024-02053-6

## Connected records

- fronts: [AI & Computation](https://onco.cc/fronts/ai-computation/)
- companies: [Google DeepMind (and Google Research)](https://onco.cc/companies/google-deepmind/)
- key papers: [Effective gene expression prediction from sequence by integrating long-range interactions](https://onco.cc/key-papers/paper-avsec-z-nat-methods/), [Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation](https://onco.cc/key-papers/paper-linder-nat-genet/)

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