Genomic Intelligence
Predict regulatory features, gene structure, and expression directly from DNA sequence...
Install
npx skills add synthetic-sciences/openscience --skill genomic-intelligence -g -a claude-code -y- Repository
- synthetic-sciences/openscience4.3k
- Category
- AI and agents
- Updated
- 6d ago
- License
- MIT
- Context cost
- Mediumabout 3,000 tokens
- Runs scripts
- No, instructions only
What it does
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.
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 ·
REST contract at 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 model inference from sequence.
Research and development use. Not for clinical or diagnostic decisions.
