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The Next AlphaFold Won’t Design Drugs. It Will Find Targets
Evolution has already generated the data. The next challenge is learning what it means.
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From Ozempic to 41 genes that shape drug response
[G×I] screened 5,317 variants near 41 pharmacogenes and identified 22 testable regulatory candidates linked to drug response.
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Genomic Intelligence is where the agents already are
Genomic Intelligence models are now callable from a growing set of agent platforms, and from any MCP client. One integration standard, a REST API and a hosted MCP server, is what made each of those a short piece of configuration rather than a project.
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[G×I] predicts 200+ candidate regulators of GLP1R expression
[G×I] expression model identifies more than 200 variants with strong predicted effects on GLP1R expression.
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Genomic Intelligence is now in the official MCP Registry
The Genomic Intelligence MCP server is now published in the official Model Context Protocol registry, so registry-aware clients can discover it by name with no configuration written by hand.
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Could your genome affect your response to Ozempic? Genomic Intelligence helps you explore it
A Nature GWAS study found a GLP1R variant linked to greater weight loss. Genomic Intelligence models suggest a second mechanism, help profile rare variants missed by GWAS, and let anyone screen their own genome.
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Genomic Intelligence models are now available in Biomni Lab
Biomni can now call Genomic Intelligence sequence-to-function models inside natural-language research workflows — turning promoter design, expression prediction, and variant interpretation into agent-executable tasks.
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Designing a glioblastoma-selective promoter with Claude Code and Genomic Intelligence
A Claude Code agent used the Genomic Intelligence expression API to screen endogenous promoters, optimize a PROM1-derived regulatory sequence, and produce a reproducible in-silico candidate for wet-lab validation.
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Why we built the Genomic Intelligence MCP server
Frontier labs are moving from chat interfaces to agentic scientific workbenches. The gi-mcp server lets any MCP agent call genome-scale models directly as tools.
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Build with Genomic Intelligence: our agentic genomics challenge
Following our ClawBio × Genomic Intelligence session, we are inviting the community to build a genomics use case on our API, MCP server, or web platform — best case wins up to $1,000.
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From raw DNA to protein: an agentic genome-annotation walkthrough
A ClawBio × Genomic Intelligence workflow takes a 120 kb region of unannotated DNA and reconstructs a gene end to end — landing on MYC at 99.77% identity.
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Finding genes in unannotated genomes with ClawBio and Genomic Intelligence
A ClawBio + Genomic Intelligence walkthrough for gene finding, splice-site annotation, CDS prediction, and protein-function inference from raw DNA sequence.
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Detecting a disease-causing promoter deletion with ClawBio and Genomic Intelligence
A reproducible ClawBio + Genomic Intelligence workflow: fetch the wild-type BMPR1A promoter, mechanically construct a patient-associated 150 bp deletion, and show the GI promoter model score drop below threshold.
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Predicting gene expression and optimizing promoters with ClawBio and Genomic Intelligence
A step-by-step walkthrough of the gi-expression skill run through ClawBio and Codex: predict HBB promoter activity in K562 and HepG2, then greedily mutate the promoter to raise predicted HepG2 expression from 0.76 to 390 TPM.
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Applications of DNA language models: from reading genomes to writing biology
The first wave of DNA language model applications is already here — variant interpretation, target discovery, genome annotation, and sequence design — and where the field could go as the models get more powerful.
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The genome is the largest dataset on Earth
The case for DNA as AI’s next frontier — why genomic data now dwarfs the internet, why text-style scaling has failed on it, and what reading the full genetic program could unlock.