[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-google-deepmind-unibind-database":3,"mdc-xq8rpu-key":33,"related-org-google-deepmind-unibind-database":1338,"related-repo-google-deepmind-unibind-database":1503},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":22,"repoUrl":23,"updatedAt":24,"license":25,"forks":26,"topics":27,"repo":28,"sourceUrl":31,"mdContent":32},"unibind-database","query UniBind for transcription factor binding sites","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\u002FFASTA) 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.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"google-deepmind","Google DeepMind","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fgoogle-deepmind.png",[12,16,19],{"name":13,"slug":14,"type":15},"Research","research","tag",{"name":17,"slug":18,"type":15},"Bioinformatics","bioinformatics",{"name":20,"slug":21,"type":15},"Genetics","genetics",2333,"https:\u002F\u002Fgithub.com\u002Fgoogle-deepmind\u002Fscience-skills","2026-07-12T07:52:11.825085",null,234,[],{"repoUrl":23,"stars":22,"forks":26,"topics":29,"description":30},[],"GDM Science Skills to speed up agentic scientific workflows with better grounding and higher token efficiency. Integrate insights from AlphaGenome, AFDB, UniProt and 30+ other databases and tools.","https:\u002F\u002Fgithub.com\u002Fgoogle-deepmind\u002Fscience-skills\u002Ftree\u002FHEAD\u002Fskills\u002Funibind_database","---\nname: unibind-database\ndescription: >-\n  Queries the UniBind database for experimentally validated transcription factor\n  (TF) binding sites. Use when retrieving direct TF-DNA interaction datasets,\n  downloading binding site coordinates (BED\u002FFASTA) for local analysis, or\n  listing available datasets by species, cell line, or TF name. Don't use to\n  query specific intervals, locations, genes, motif models or expression\n  data.\n---\n\n# UniBind Database Skill\n\nUniBind is a database of direct TF–DNA interactions across 9 species,\nintegrating ChIP-seq peaks with JASPAR TF binding profiles via the DAMO\nframework.\n\n## Prerequisites\n\n1.  **`uv`**: Read the `uv` skill and follow its Setup instructions to ensure\n    `uv` is installed and on PATH.\n2.  **User Notification**: If .licenses\u002Funibind_database_LICENSE.txt does not\n    already exist in the workspace root directory then (1) prominently notify\n    the user to check the terms at https:\u002F\u002Funibind.uio.no\u002F and\n    https:\u002F\u002Funibind.uio.no\u002Fapi\u002Foverview, then (2) create the file recording the\n    notification text and timestamp.\n\n## Quick Start\n\nQuery commands print JSON to stdout by default. Most outputs are small enough to\nread directly. For large outputs (`list_cell_lines`, `list_tfs`), pipe through\n`jq` to extract only the fields you need.\n\n```bash\nuv run \u003CSKILL DIR>\u002Fscripts\u002Funibind_api.py list_species\n```\n\nThe `download_tfbs` command writes BED\u002FFASTA files to `--output-dir` instead.\nYou may optionally use `--output \u003Cpath>` on any query command to save results to\na file if needed.\n\n## Core Rules\n\n-   **Use the Wrapper**: ALWAYS execute the provided helper scripts to query the\n    database rather than accessing the database directly. The scripts\n    automatically enforce the required rate limit gracefully.\n-   **Output**: Query commands print JSON to stdout. Most responses are compact\n    and can be read directly.\n-   **Large Results**: `list_cell_lines` and `list_tfs` produce large output.\n    Pipe these through `jq` to extract specific fields rather than reading the\n    full output into context.\n-   **Saving to File**: Use `--output \u003Cpath>` when you need to reference the\n    data later or when processing very large results with `jq`.\n-   **Pagination**: Use `--page` and `--page-size` (max 1000) to chunk large\n    result sets.\n-   **Ordering**: Use `--order field_name` (prefix with `-` for descending) on\n    any list command.\n-   **Notification**: If this skill is used, ensure this is mentioned in the\n    output.\n\n## Utility Scripts\n\n*Replace `\u003CSKILL DIR>` with the absolute path to this skill's directory.*\n\n### 1. List Species\n\n```bash\nuv run \u003CSKILL DIR>\u002Fscripts\u002Funibind_api.py list_species\n```\n\n### 2. List Collections\n\n```bash\nuv run \u003CSKILL DIR>\u002Fscripts\u002Funibind_api.py list_collections\n```\n\n### 3. List Cell Lines & TFs (large output — use `jp`)\n\nThese commands return large datasets. Use `uvx --from jmespath jp` to extract\nonly the fields you need.\n\n```bash\nuv run \u003CSKILL DIR>\u002Fscripts\u002Funibind_api.py list_cell_lines | uvx --from jmespath jp \"results[].name\"\nuv run \u003CSKILL DIR>\u002Fscripts\u002Funibind_api.py list_tfs | uvx --from jmespath jp \"results[].tf_name\"\n```\n\n### 4. List and Filter Datasets (and Profile-Specific Datasets)\n\nFilter datasets using the following arguments:\n\n-   `--species` (e.g., \"Homo sapiens\")\n-   `--tf-name` (e.g., \"CTCF\")\n-   `--cell-line` (e.g., \"mESC\")\n-   `--collection` (e.g., Permissive, Robust)\n-   `--search` (a search term)\n-   `--biological-condition` (biological condition or source)\n-   `--data-source` (source of data, e.g., \"ENCODE\")\n-   `--has-pvalue` (\"true\" or \"false\")\n-   `--identifier` (e.g., \"GSE60130\")\n-   `--jaspar-id` (JASPAR database profile matrix ID)\n-   `--model` (prediction model)\n-   `--summary` (summary filter)\n-   `--threshold-pvalue` (p-value threshold)\n\nUse `list_datasets` for standard datasets, or `list_specific_datasets` for\nprofile-specific queries.\n\n```bash\nuv run \u003CSKILL DIR>\u002Fscripts\u002Funibind_api.py list_datasets --species \"Homo sapiens\" --tf-name \"CTCF\" --data-source \"ENCODE\"\nuv run \u003CSKILL DIR>\u002Fscripts\u002Funibind_api.py list_specific_datasets --species \"Mus musculus\" --cell-line \"mESC\"\n```\n\n### 5. Get Dataset Details\n\n```bash\nuv run \u003CSKILL DIR>\u002Fscripts\u002Funibind_api.py get_dataset \"EXP047889.HMLE-Twist-ER_breast_cancer.SMAD3\"\n```\n\n### 6. Download TFBS Files (BED \u002F FASTA)\n\nDownloads all TFBS files for a dataset to a local directory. Use `--format bed`\n(default) or `--format fasta`.\n\n```bash\nuv run \u003CSKILL DIR>\u002Fscripts\u002Funibind_api.py download_tfbs \"EXP047889.HMLE-Twist-ER_breast_cancer.SMAD3\" --output-dir \u002Ftmp\u002Ftfbs --format bed\n```\n\n## Anti-Patterns\n\n-   **DON'T** attempt to use the UniBind API to query specific genomic\n    intervals, locations, or genes.\n-   **DON'T** guess or hallucinate genome coordinates. Always use\n    `ensembl-database` as an external check if you're pulling local BED tracks\n    for offline bedtools intersection.\n-   **DON'T** use for motif models (PFMs). Use the **jaspar-database** skill\n    instead.\n-   **DON'T** use for gene expression data. UniBind only stores binding events.\n-   **DON'T** assume tissue-specific expression from dataset lists alone.\n-   **DON'T** use `cat` to read large JSON output files into context. The output\n    is too large. 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Use ",{"type":39,"tag":73,"props":1326,"children":1328},{"className":1327},[],[1329],{"type":45,"value":155},{"type":45,"value":1331}," or write your own code to parse the output files.",{"type":39,"tag":1333,"props":1334,"children":1335},"style",{},[1336],{"type":45,"value":1337},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":1339,"total":1502},[1340,1355,1368,1388,1400,1415,1431,1444,1456,1471,1481,1491],{"slug":1341,"name":1341,"fn":1342,"description":1343,"org":1344,"tags":1345,"stars":22,"repoUrl":23,"updatedAt":1354},"alphafold-database-fetch-and-analyze","retrieve and analyze AlphaFold protein structures","Retrieve and analyze AlphaFold predicted structures for a protein. Use when the user provides a specific UniProt Accession ID and wants structural confidence metrics (pLDDT), domain boundary analysis, or disorder assessment. Do not use if the user only has a protein name, gene name, or amino acid sequence — ask for a UniProt ID first.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1346,1347,1350,1353],{"name":17,"slug":18,"type":15},{"name":1348,"slug":1349,"type":15},"Genomics","genomics",{"name":1351,"slug":1352,"type":15},"Life Sciences","life-sciences",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:51.827211",{"slug":1356,"name":1356,"fn":1357,"description":1358,"org":1359,"tags":1360,"stars":22,"repoUrl":23,"updatedAt":1367},"alphagenome-single-variant-analysis","analyze genetic variant effects with AlphaGenome","Analyzes genetic variant effects on gene expression (RNA-seq), chromatin accessibility (DNASE), histone marks (ChIP), and transcription factors using the AlphaGenome API. Use when the user asks about non-coding variant effects, pathogenicity, clinical significance, disease associations, functional effects, gene expression changes, splicing disruption, or regulatory effects in promoters and enhancers. Also use for resolving biological terms to tissue\u002Fcell-type ontologies (UBERON\u002FCL) or analyzing variants in chr:pos:ref>alt format.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1361,1362,1363,1364],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},{"name":1365,"slug":1366,"type":15},"RNA-seq","rna-seq","2026-07-12T07:51:39.494803",{"slug":1369,"name":1369,"fn":1370,"description":1371,"org":1372,"tags":1373,"stars":22,"repoUrl":23,"updatedAt":1387},"chembl-database","query ChEMBL database for bioactive molecules","Query the ChEMBL database for bioactive molecules, drug targets, bioactivity data, approved drugs, and chemical structures. Use when the user asks about compounds, targets, IC50\u002FKi values, drug mechanisms, or structure searches.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1374,1377,1380,1383,1386],{"name":1375,"slug":1376,"type":15},"ChEMBL","chembl",{"name":1378,"slug":1379,"type":15},"Chemistry","chemistry",{"name":1381,"slug":1382,"type":15},"Database","database",{"name":1384,"slug":1385,"type":15},"Pharmacology","pharmacology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:35.544306",{"slug":1389,"name":1389,"fn":1390,"description":1391,"org":1392,"tags":1393,"stars":22,"repoUrl":23,"updatedAt":1399},"clinical-trials-database","query clinical trial data","Query ClinicalTrials.gov via APIv2. Use when you want to search for trials by condition, drug, location, status, or phase; retrieve trial details by NCT ID; check eligibility\u002Finclusion criteria; count trials across conditions or time periods; identify a sponsor's trial portfolio; find recruiting trials for patient matching.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1394,1397,1398],{"name":1395,"slug":1396,"type":15},"Clinical Trials","clinical-trials",{"name":1351,"slug":1352,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:06.846705",{"slug":1401,"name":1401,"fn":1402,"description":1403,"org":1404,"tags":1405,"stars":22,"repoUrl":23,"updatedAt":1414},"clinvar-database","retrieve clinical significance from ClinVar database","Use when needing clinical significance, pathogenicity classifications (e.g., Pathogenic, Benign, VUS), clinical evidence rationales, or finding \"hard positive\" benchmark controls for human genomic variants.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1406,1409,1410,1413],{"name":1407,"slug":1408,"type":15},"ClinVar","clinvar",{"name":20,"slug":21,"type":15},{"name":1411,"slug":1412,"type":15},"Healthcare","healthcare",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:36.86094",{"slug":1416,"name":1416,"fn":1417,"description":1418,"org":1419,"tags":1420,"stars":22,"repoUrl":23,"updatedAt":1430},"credentials","manage and verify API credentials safely","Instructions for handling API keys and credentials safely, verifying their presence, and prompting the user to add them if missing using a safe protocol.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1421,1424,1427],{"name":1422,"slug":1423,"type":15},"Compliance","compliance",{"name":1425,"slug":1426,"type":15},"Operations","operations",{"name":1428,"slug":1429,"type":15},"Security","security","2026-07-12T07:52:17.355491",{"slug":1432,"name":1432,"fn":1433,"description":1434,"org":1435,"tags":1436,"stars":22,"repoUrl":23,"updatedAt":1443},"dbsnp-database","search genetic variants in dbSNP database","Use when you want to look up, map, and search for short genetic variants (SNPs, indels) in NCBI's dbSNP database. Resolves between rsIDs, genomic coordinates in VCF format, and HGVS strings. For an rsID, returns variant type, gene associations, clinical significance, allele frequencies, and genomic coordinates (GRCh38).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1437,1438,1439,1442],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":1440,"slug":1441,"type":15},"NCBI","ncbi",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:33.054229",{"slug":1445,"name":1445,"fn":1446,"description":1447,"org":1448,"tags":1449,"stars":22,"repoUrl":23,"updatedAt":1455},"embl-ebi-ols","search biomedical ontologies in EMBL-EBI OLS","Query and search the EMBL-EBI Ontology Lookup Service (OLS) for biomedical ontology terms, definitions, and hierarchies across 250+ ontologies (e.g., GO, DOID, HP). Use when the user asks to search for terms, retrieve details, navigate hierarchies (parents, children, ancestors), look up properties and individuals, get autocomplete suggestions, or access ontology metadata and statistics.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1450,1451,1454],{"name":17,"slug":18,"type":15},{"name":1452,"slug":1453,"type":15},"Ontology","ontology",{"name":13,"slug":14,"type":15},"2026-07-12T07:51:59.368324",{"slug":1457,"name":1457,"fn":1458,"description":1459,"org":1460,"tags":1461,"stars":22,"repoUrl":23,"updatedAt":1470},"encode-ccres-database","query ENCODE regulatory and experimental data","Query the ENCODE Registry of cis-Regulatory Elements (cCREs) via the SCREEN GraphQL API, or make custom queries to the ENCODE Portal REST API for experiments and files (ChIP-seq peaks, etc.). Use when you want to query regulatory annotations or raw experimental data across human cell types.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1462,1463,1466,1467],{"name":17,"slug":18,"type":15},{"name":1464,"slug":1465,"type":15},"GraphQL","graphql",{"name":13,"slug":14,"type":15},{"name":1468,"slug":1469,"type":15},"REST API","rest-api","2026-07-12T07:52:10.597139",{"slug":1271,"name":1271,"fn":1472,"description":1473,"org":1474,"tags":1475,"stars":22,"repoUrl":23,"updatedAt":1480},"query genomic and protein data from Ensembl","Query the Ensembl database to resolve gene, transcript, and protein IDs, fetch genomic or protein sequences, retrieve gene structures (exons), and get variant consequence and effect predictions (VEP). Use this skill as a primary ID translator, genomic sequence database and variant effect prediction tool.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1476,1477,1478,1479],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":1351,"slug":1352,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:41.645835",{"slug":1482,"name":1482,"fn":1483,"description":1484,"org":1485,"tags":1486,"stars":22,"repoUrl":23,"updatedAt":1490},"foldseek-structural-search","perform 3D protein structural searches","Performs 3D structural searches of proteins against various databases (PDB, AlphaFold, CATH, MGnify, etc.) using the Foldseek API. Use ONLY when the user provides a physical 3D coordinate file (.cif, .mmcif, or .pdb) and wants to find structurally similar proteins. Do NOT use if the user only provides a protein sequence, gene name, or UniProt ID.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1487,1488,1489],{"name":17,"slug":18,"type":15},{"name":1351,"slug":1352,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:52:09.354992",{"slug":1492,"name":1492,"fn":1493,"description":1494,"org":1495,"tags":1496,"stars":22,"repoUrl":23,"updatedAt":1501},"gnomad-database","query genetic variant data from gnomAD","Query the Genome Aggregation Database (gnomAD). Use when determining the rarity or allele frequency of specific genetic variants, retrieving gene constraint metrics (pLI, LOEUF) to assess loss-of-function intolerance, finding variants in a genomic region or gene, or querying structural variants. Don't use for analyzing individual patient genomes, tracking somatic mutations in cancer (use COSMIC), or requesting raw sequencing reads (use ENA).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1497,1498,1499,1500],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":1351,"slug":1352,"type":15},{"name":13,"slug":14,"type":15},"2026-07-12T07:51:38.213009",38,{"items":1504,"total":1502},[1505,1512,1519,1527,1533,1540,1546],{"slug":1341,"name":1341,"fn":1342,"description":1343,"org":1506,"tags":1507,"stars":22,"repoUrl":23,"updatedAt":1354},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1508,1509,1510,1511],{"name":17,"slug":18,"type":15},{"name":1348,"slug":1349,"type":15},{"name":1351,"slug":1352,"type":15},{"name":13,"slug":14,"type":15},{"slug":1356,"name":1356,"fn":1357,"description":1358,"org":1513,"tags":1514,"stars":22,"repoUrl":23,"updatedAt":1367},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1515,1516,1517,1518],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":13,"slug":14,"type":15},{"name":1365,"slug":1366,"type":15},{"slug":1369,"name":1369,"fn":1370,"description":1371,"org":1520,"tags":1521,"stars":22,"repoUrl":23,"updatedAt":1387},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1522,1523,1524,1525,1526],{"name":1375,"slug":1376,"type":15},{"name":1378,"slug":1379,"type":15},{"name":1381,"slug":1382,"type":15},{"name":1384,"slug":1385,"type":15},{"name":13,"slug":14,"type":15},{"slug":1389,"name":1389,"fn":1390,"description":1391,"org":1528,"tags":1529,"stars":22,"repoUrl":23,"updatedAt":1399},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1530,1531,1532],{"name":1395,"slug":1396,"type":15},{"name":1351,"slug":1352,"type":15},{"name":13,"slug":14,"type":15},{"slug":1401,"name":1401,"fn":1402,"description":1403,"org":1534,"tags":1535,"stars":22,"repoUrl":23,"updatedAt":1414},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1536,1537,1538,1539],{"name":1407,"slug":1408,"type":15},{"name":20,"slug":21,"type":15},{"name":1411,"slug":1412,"type":15},{"name":13,"slug":14,"type":15},{"slug":1416,"name":1416,"fn":1417,"description":1418,"org":1541,"tags":1542,"stars":22,"repoUrl":23,"updatedAt":1430},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1543,1544,1545],{"name":1422,"slug":1423,"type":15},{"name":1425,"slug":1426,"type":15},{"name":1428,"slug":1429,"type":15},{"slug":1432,"name":1432,"fn":1433,"description":1434,"org":1547,"tags":1548,"stars":22,"repoUrl":23,"updatedAt":1443},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[1549,1550,1551,1552],{"name":17,"slug":18,"type":15},{"name":20,"slug":21,"type":15},{"name":1440,"slug":1441,"type":15},{"name":13,"slug":14,"type":15}]