unibind-database
Queries the UniBind database for experimentally validated transcription factor (TF) binding sites. Use when retrieving direct TF-DNA interaction datasets, downloading binding site coordinates (BED/FASTA) for local analysis, or listing available datasets by species, cell line, or TF name. Don't use to query specific intervals, locations, genes, motif models or expression data.
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/google-deepmind/science-skills --skill unibind-database- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads unibind-database automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
UniBind Database Skill
UniBind is a database of direct TF–DNA interactions across 9 species, integrating ChIP-seq peaks with JASPAR TF binding profiles via the DAMO framework.
Prerequisites
uv: Read theuvskill and follow its Setup instructions to ensureuvis installed and on PATH.- User Notification: If .licenses/unibind_database_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://unibind.uio.no/ and https://unibind.uio.no/api/overview, then (2) create the file recording the notification text and timestamp.
Quick Start
Query commands print JSON to stdout by default. Most outputs are small enough to
read directly. For large outputs (list_cell_lines, list_tfs), pipe through
jq to extract only the fields you need.
uv run <SKILL DIR>/scripts/unibind_api.py list_species
The download_tfbs command writes BED/FASTA files to --output-dir instead.
You may optionally use --output <path> on any query command to save results to
a file if needed.
Core Rules
- Use the Wrapper: ALWAYS execute the provided helper scripts to query the database rather than accessing the database directly. The scripts automatically enforce the required rate limit gracefully.
- Output: Query commands print JSON to stdout. Most responses are compact and can be read directly.
- Large Results:
list_cell_linesandlist_tfsproduce large output. Pipe these throughjqto extract specific fields rather than reading the full output into context. - Saving to File: Use
--output <path>when you need to reference the data later or when processing very large results withjq. - Pagination: Use
--pageand--page-size(max 1000) to chunk large result sets. - Ordering: Use
--order field_name(prefix with-for descending) on any list command. - Notification: If this skill is used, ensure this is mentioned in the output.
Utility Scripts
Replace <SKILL DIR> with the absolute path to this skill's directory.
1. List Species
uv run <SKILL DIR>/scripts/unibind_api.py list_species
2. List Collections
uv run <SKILL DIR>/scripts/unibind_api.py list_collections
3. List Cell Lines & TFs (large output — use jp)
These commands return large datasets. Use uvx --from jmespath jp to extract
only the fields you need.
uv run <SKILL DIR>/scripts/unibind_api.py list_cell_lines | uvx --from jmespath jp "results[].name"
uv run <SKILL DIR>/scripts/unibind_api.py list_tfs | uvx --from jmespath jp "results[].tf_name"
4. List and Filter Datasets (and Profile-Specific Datasets)
Filter datasets using the following arguments:
--species(e.g., "Homo sapiens")--tf-name(e.g., "CTCF")--cell-line(e.g., "mESC")--collection(e.g., Permissive, Robust)--search(a search term)--biological-condition(biological condition or source)--data-source(source of data, e.g., "ENCODE")--has-pvalue("true" or "false")--identifier(e.g., "GSE60130")--jaspar-id(JASPAR database profile matrix ID)--model(prediction model)--summary(summary filter)--threshold-pvalue(p-value threshold)
Use list_datasets for standard datasets, or list_specific_datasets for
profile-specific queries.
uv run <SKILL DIR>/scripts/unibind_api.py list_datasets --species "Homo sapiens" --tf-name "CTCF" --data-source "ENCODE"
uv run <SKILL DIR>/scripts/unibind_api.py list_specific_datasets --species "Mus musculus" --cell-line "mESC"
5. Get Dataset Details
uv run <SKILL DIR>/scripts/unibind_api.py get_dataset "EXP047889.HMLE-Twist-ER_breast_cancer.SMAD3"
6. Download TFBS Files (BED / FASTA)
Downloads all TFBS files for a dataset to a local directory. Use --format bed
(default) or --format fasta.
uv run <SKILL DIR>/scripts/unibind_api.py download_tfbs "EXP047889.HMLE-Twist-ER_breast_cancer.SMAD3" --output-dir /tmp/tfbs --format bed
Anti-Patterns
- DON'T attempt to use the UniBind API to query specific genomic intervals, locations, or genes.
- DON'T guess or hallucinate genome coordinates. Always use
ensembl-databaseas an external check if you're pulling local BED tracks for offline bedtools intersection. - DON'T use for motif models (PFMs). Use the jaspar-database skill instead.
- DON'T use for gene expression data. UniBind only stores binding events.
- DON'T assume tissue-specific expression from dataset lists alone.
- DON'T use
catto read large JSON output files into context. The output is too large. Usejqor write your own code to parse the output files.
FAQ
What does the unibind-database skill do?
Queries the UniBind database for experimentally validated transcription factor (TF) binding sites. Use when retrieving direct TF-DNA interaction datasets, downloading binding site coordinates (BED/FASTA) for local analysis, or listing available datasets by species, cell line, or TF name. Don't use to query specific intervals, locations, genes, motif models or expression data.
How do I install unibind-database?
Run npx skills add https://github.com/google-deepmind/science-skills --skill unibind-database in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/unibind-database/ (personal) or .claude/skills/unibind-database/ (project).
Which AI agents can use unibind-database?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is unibind-database safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains unibind-database?
It is published by google-deepmind in google-deepmind/science-skills. It has 2,108 recorded installs.
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