genomic-intelligence

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Predict regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no local GPU or model weights. Six tasks over a REST API and a hosted MCP server (keyless public demo): promoter regions, splice donor/acceptor sites, enhancer activity, chromatin state, sequence-to-expression (log TPM), and de-novo gene annotation, plus a composite find-genes-then-predict-expression workflow. Use when the user has a gene symbol, a genomic region, or a DNA/FASTA sequence and wants any of these predictions, mentions Genomic Intelligence, genomicintelligence.ai, api.genomicintelligence.ai, or mcp.genomicintelligence.ai.

AI & Automation 46,700 stars 4221 forks Updated 5 days ago MIT

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Skill Content

# Genomic Intelligence — DNA Sequence Models Genomic Intelligence (GI) serves transformer DNA language models over six sequence-analysis tasks on managed GPUs. Give it a **gene symbol**, a **genomic region**, or a **DNA/FASTA sequence**; it returns structured predictions — promoter regions, splice sites, enhancer activity, chromatin state, expression (log TPM), and de-novo gene annotation. Nothing runs locally: no model weights, no GPU, no heavy Python stack. It is a thin client over a hosted, versioned inference API. **Official docs:** [docs.genomicintelligence.ai](https://docs.genomicintelligence.ai) · REST contract at [api.genomicintelligence.ai/v1/openapi.json](https://api.genomicintelligence.ai/v1/openapi.json) · hosted MCP server at `https://mcp.genomicintelligence.ai/mcp` ## When to use this skill Use GI when the user has DNA and wants a model prediction: - **Find promoters** in a genomic region (`promoter`) - **Predict splice** donor/acceptor sites (`splice`) - **Score enhancer activity** — developmental & housekeeping (`enhancer`) - **Annotate chromatin state** across hundreds of tracks (`chromatin`) - **Predict expression** as log(TPM+1) from a sequence + cell-type context (`expression`) - **Annotate genes/transcripts** de novo, no reference needed (`annotation`) - **Find the genes in a region and predict each one's expression** (composite) Not for local alignment, variant calling, or file I/O — use a local tool (BioPython, bcftools) for those. GI is for **mod...

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Author
K-Dense-AI
Repository
K-Dense-AI/scientific-agent-skills
Created
11 months ago
Last Updated
5 days ago
Language
Python
License
MIT

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