### Jaspar Database
Works with
name: "jaspar-database"
description: "Query the JASPAR database for Transcription Factor (TF) binding profiles. Use when retrieving Position Frequency Matrices (PFMs) or Position Weight Matrices (PWMs) for specific TFs, resolving gene sym..."
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Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionjaspar-databaseExecute the skills CLI command in your project's root directory to begin installation:
Fetches jaspar-database from google-deepmind/science-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate jaspar-database. Access via /jaspar-database in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
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| name | jaspar-database |
| description | > Query the JASPAR database for Transcription Factor (TF) binding profiles. Use when retrieving Position Frequency Matrices (PFMs) or Position Weight Matrices (PWMs) for specific TFs, resolving gene symbols to JASPAR Matrix IDs, or getting TF metadata. Supports multiple output formats (MEME, TRANSFAC, PFM, JASPAR, YAML). |
JASPAR is the definitive open-access database for Transcription Factor (TF) binding profiles, stored as Position Frequency Matrices (PFMs).
Use this skill to map abstract sequence motifs or genomic regions to specific biological regulators (e.g., "what TFs bind here?" or "what is the motif for CTCF?").
uv: Read the uv skill and follow its Setup instructions to ensure
uv is installed and on PATH.CRITICAL: You MUST respect the JASPAR API Terms of Use by adhering to the following:
jaspar_api.py script automatically
chunks larger requests for you to bypass this limitation when querying
larger regions.get_tf_motif, get_tf_metadata, and get_tf_pwm
require a stable JASPAR Matrix ID (e.g., MA0488.2). If a user provides a
gene symbol (e.g., JUN), you must resolve it first using resolve_tf_id.tax_id to ensure targeted
searches. Common IDs: Human=9606, Mouse=10090.Run all commands using the bundled Python script:
Maps a transcription factor name to a stable Matrix ID. Required step before fetching motifs if only a gene name is provided.
uv run scripts/jaspar_api.py resolve_tf_id --name "JUN" --tax-id 9606
Retrieves the raw Position Frequency Matrix for a specific TF. Supports
--format flag.
uv run scripts/jaspar_api.py get_tf_motif --matrix-id "MA0488.2"
uv run scripts/jaspar_api.py get_tf_motif --matrix-id "MA0488.2" --format meme
Retrieves TF class, family, and links to external databases (e.g., UniProt).
Supports --format flag.
uv run scripts/jaspar_api.py get_tf_metadata --matrix-id "MA0488.2"
uv run scripts/jaspar_api.py get_tf_metadata --matrix-id "MA0488.2" --format yaml
Fetches the PFM for a matrix and converts it to log-odds scores (PWM).
uv run scripts/jaspar_api.py get_tf_pwm --matrix-id "MA0488.2"
uv run scripts/jaspar_api.py get_tf_pwm --matrix-id "MA0488.2" --pseudocount 0.1
Infers potential JASPAR matrix profiles from a raw transcription factor protein sequence.
uv run scripts/jaspar_api.py infer_from_sequence --sequence "QAQLLPSHHVG"
Retrieves metadata for a JASPAR TF Flexible Model. (Note: The JASPAR TFFM endpoints occasionally experience 500 Internal Server errors).
uv run scripts/jaspar_api.py get_tffm --tffm-id "TFFM0001.1"
The get_tf_motif and get_tf_metadata commands accept an optional --format
flag. Supported formats: json (default), jsonp, jaspar, meme,
transfac, pfm, yaml.
JUN) to get_tf_motif. You must pass
the MA... Matrix ID.--tax-id when resolving a TF name.Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
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✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
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Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
google-deepmind/science-skills
google-deepmind/science-skills
google-deepmind/science-skills
K-Dense-AI/scientific-agent-skills
K-Dense-AI/scientific-agent-skills
K-Dense-AI/scientific-agent-skills
Keeps context tight: jaspar-database is the kind of skill you can hand to a new teammate without a long onboarding doc.
jaspar-database reduced setup friction for our internal harness; good balance of opinion and flexibility.
jaspar-database is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
I recommend jaspar-database for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
jaspar-database has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: jaspar-database is focused, and the summary matches what you get after install.
I recommend jaspar-database for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
Registry listing for jaspar-database matched our evaluation — installs cleanly and behaves as described in the markdown.
Keeps context tight: jaspar-database is the kind of skill you can hand to a new teammate without a long onboarding doc.
jaspar-database reduced setup friction for our internal harness; good balance of opinion and flexibility.
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