Building biology AI models autonomously
Biomni x TusoAI is an autonomous, code‑free platform that develops computational biology methods from a single natural‑language prompt. The system coordinates agents to search over both data and code, iterating hundreds of times per dollar without requiring environment setup or programming. It has demonstrated state‑of‑the‑art performance on tasks such as enhancer‑gene linking and genetic perturbation prediction, and is released as open‑source software.
- ▪Biomni x TusoAI automates the entire method‑development cycle, allowing users to specify goals in one sentence of natural language.
- ▪The platform simultaneously searches over data sources and code repositories, iterating thousands of times autonomously to improve model performance.
- ▪In benchmark tests for genetic perturbation prediction, the system discovered a simple ensemble approach that outperformed larger deep‑learning models across most metrics.
- ▪Biomni x TusoAI and its underlying TusoAI code are publicly available on GitHub and can be accessed without any coding or environment configuration.
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| Original publisher | Phylo |
| Canonical URL | https://phylo.bio/blog/biomni-tuso |
| Publication time | Sat, 01 Aug 2026 12:11:32 +0000 |
| Retrieval time | 2026-08-01T12:23:26.556Z |
| Last seen | 2026-08-01T12:23:26.556Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | zsAs8AfbUzN_ · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
« backBuilding state-of-the-art biology AI models autonomouslyBy PhyloWe present Biomni x TusoAI, a fully autonomous and code-free tool for method development in biology — building state-of-the-art models for genetic perturbation prediction and enhancer-gene linking from a single sentence of natural language.Jul 30, 20265 min readComputational methods are needed across all fields of biology and are central to discovery, but their slow development leads to a vast amount of experimental data remaining underutilized and poorly understood.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Phylo.
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