99Science · AI & science

SCIENCE UNDER AUTOMATION

AI in Computational genomics: capabilities and evidence

A large part of the work already happens inside software. The difficult boundary is between executing an analysis and knowing whether it answers the biological question.

What has AI demonstrated?

0.48 artifact-based score

Test
20 study-scale tasks, 138 output artifacts; GPT 5.6 Sol in the cited BixBench3 version.
Comparison
13 models evaluated; no matched human baseline extracted.
System and version
BixBench3 · v2, September 2026
Evidence checked
2026-10-20

Scientists supply objectives and methodological guidance. Artifact score is not fraction of studies autonomously completed.

What does the field require?

Analyse an existing study from raw data

Discover and validate a new genomic mechanism

Research tasks

Run a specified analysis

Closest match to the seeded benchmark: objectives and methodological guidance are supplied.

Design a new biological study

Question quality, confounding and validation require separate evidence.

Validate a new mechanism

Often crosses from computation into experiments; the field-level physical rating no longer applies.

Can AI replace the whole workflow?

The results above measure specific tasks. The field assessment also requires completion of the connected workflow, including the requirements listed here. A field-wide replacement percentage has not been established.

Read the assessment method

Sources and related evidence

Compare related fields

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