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BIO·ATLASby Bayes Pharma.ai
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AI drug discovery models/Genomics, DNA & RNA/Borzoi
model-family passport · Review date not recorded

Borzoi

DNA-to-RNA regulatory modelling across cell and tissue contexts.

4/7Evidence fields documented
60-SECOND EVALUATION VIEW

What should a scientist know before using Borzoi?

SupportedEvidence supports the stated context with explicit boundaries
Best suited forPrediction · Variant effect
Evidence supportsFunctional-genomics and RNA-seq evaluations: Peer-reviewed
Evidence does not establishUniversal superiority, therapeutic success, clinical utility or regulatory acceptance.
Major limitationPerformance depends on the evaluation dataset and operating conditions.
CompareAdd to evaluationView evidence
Current registry recordVersion history not yet curated1 recorded release · Review date not recorded. A newer version is not assumed to be universally better.

What it is

Borzoi predicts RNA-seq coverage and transcript-resolved regulatory consequences from long DNA sequence.

Evidence trail

BioAtlas keeps the path from source to decision visible. A connection records provenance; it does not imply that evidence is sufficient for every context.

Sources3 connectedPrimary resources and normalized claims
Claims1 normalizedGenomic sequence modelling
EntityBorzoimodel-family · Version history not yet curated
ReviewReview date not recordedReview date not claimed
ConclusionContext requiredAdd to an evaluation before operational use

Model passport

Entity typemodel-family
OrganizationCalico / academic collaborators
Model family introducedNot normalized
AccessOpen source
Commercial useAllowed / verify checkpoint terms
DeploymentSelf-hosted
ComputeGPU recommended
Domainsgenomics · rna
Biology → representation → computation → evidence

How Borzoi represents biology

model-familygenomicsrna

Category is navigation. These fields describe the model-specific computational transformation and deliberately override broad category defaults.

1 · Biological inputs
Long DNA sequence
2 · Input representation
Nucleotide sequence
3 · Internal representation
Regulatory sequence features
4 · Architecture
Long-context sequence model
5 · Learning objective
Supervised functional-genomics prediction
6 · Output representation
Genomic tracksScores

Biological scale

genomegenetranscript

Modalities & tasks

DNARNAPredictionVariant effect

Registry, claims and frontier intelligence

Versioned registry

Version history not yet curated

1 version record · release year not yet normalized. Model-family identity remains separate from capability and access changes.

Explore version lineage →
Benchmark claim ledger

1 normalized claim

Genomic sequence modelling · Functional-genomics and RNA-seq evaluations

Open claim intelligence →

Inputs and outputs

Inputs

Long DNA sequence

Outputs

RNA-seq coverageRegulatory / variant-effect predictions

Scientific and technical profile

Scientific principles

Regulatory genomicsSequence-to-expression prediction

Technology

Long-context sequence modelMulti-track genomic outputs
Ideas before algorithms

Scientific lineage

Explore all foundations

These are transparent concept matches—not claims that one scientist alone caused this model. Each connection is based on the model’s recorded domain, scientific principles, technical terms or an explicit lineage link.

Genomics & cell systems

DNA as the hereditary transforming principle

Oswald Avery, Colin MacLeod & Maclyn McCarty

Genomics, variant interpretation, gene therapy and sequence foundation models depend on DNA being the durable molecular carrier of biological information.

Matched concepts: dna, sequence, variant
Genomics & cell systems

Gene regulation and the operon model

François Jacob & Jacques Monod

Target biology, perturbation models, transcriptomic response prediction and virtual cells all require an explicit model of regulated gene programs.

Matched concepts: expression, transcript, regulatory
Genomics & cell systems

X-ray evidence for the helical structure of DNA

Rosalind Franklin & Raymond Gosling

Structural genomics and sequence-to-structure reasoning began with experimentally grounded molecular geometry.

Matched concepts: dna, sequence
Genomics & cell systems

Reading the sequences of proteins and DNA

Frederick Sanger

Biological foundation models exist because proteins and genomes became readable, comparable and computable at scale.

Matched concepts: sequence, dna

Evaluation evidence

Dataset or evaluationFunctional-genomics and RNA-seq evaluations
Task or metricSequence-to-RNA prediction
Evidence statusPeer-reviewed
Open source ↗

Task-specific evidence only; not comparable as a universal leaderboard score.

Genomic sequence modelling

Functional-genomics and RNA-seq evaluations

Version history not yet curated · Split details not yet normalized
peer-reviewed

A structured benchmark claim is recorded; consult the linked source for numeric values and protocol details.

Claim caveats
  • Protocol, split and implementation details must match before comparing this claim with another result.
Open benchmark claim →

Known limitations

  • Performance depends on the evaluation dataset and operating conditions.
  • Task-specific benchmark results should not be compared across unlike domains.
  • Outputs require task-specific scientific and experimental validation.

Milestones

Not normalized

Connects DNA sequence to tissue-specific RNA readouts.