Genomics · Database
JASPAR
A curated database of non-redundant transcription factor binding profiles across eukaryotic taxa.
What JASPAR is
JASPAR is an open-access genomics database containing curated, non-redundant transcription factor (TF) binding profiles derived from published collections of experimentally defined binding sites across eukaryotes. Introduced in 2004, the resource provides computational and experimental biologists with standardised binding specificity models for investigating transcriptional regulation.
The resource addresses the need for high-quality sequence motifs when analysing cis-regulatory architecture, identifying binding sites, or mapping factor interactions across diverse organisms. It covers structural classes and families of transcription factors across multiple eukaryotic kingdoms, ranging from vertebrates and plants to fungi and nematodes.
JASPAR organises its data into collections, primarily the curated JASPAR CORE dataset as well as unvalidated profiles and deep learning models. It supports motif discovery and sequence analysis through web tools, programmatic interfaces, and direct batch downloads.
How it is organised
Binding profiles in JASPAR are constructed from published experimental assays, including ChIP-seq, HT-SELEX, PBM, DAP-seq, CUT&RUN, and macromolecular footprinting techniques. The curated binding profiles are stored as position frequency matrices (PFMs), from which position-specific weight matrices (PWMs) can be computed, as well as transcription factor flexible models (TFFMs).
Profiles are systematically organised by taxonomic groups, structural classes (such as basic leucine zipper factors, basic helix-loop-helix factors, and zinc finger proteins), and families. Users can explore data through dedicated tools such as Matrix Align, enrichment analysis, matrix clustering, and genome tracks, or query the resource programmatically via a RESTful API and the pyJASPAR Python interface.
Key facts
- Category
- Genomics database
- Primary contents
- Transcription factor binding profiles
- Data representations
- Position frequency matrices (PFM), transcription factor flexible models (TFFM), position-specific weight matrices (PWM)
- Taxonomic scope
- Vertebrates, plants, insects, nematodes, fungi, and urochordates
- Assay types represented
- ChIP-seq, CUT&RUN, HT-SELEX, DAP-seq, PBM, EMSA, DNaseI footprinting, SELEX-seq, SMiLE-seq, and hybrid assays
- Collections
- JASPAR CORE, JASPAR UNVALIDATED, and JASPAR Deep Learning
- Access interfaces
- Web interface, RESTful API, pyJASPAR Python library, batch download
What you can use it for
- Transcription factor binding site prediction
- Scan genomic regions or promoter sequences with PFMs, PWMs, or TFFMs to identify putative regulatory binding sites for specific transcription factors.
- Motif comparison and alignment
- Use the Matrix Align and matrix clustering tools to evaluate sequence similarity between newly discovered DNA motifs and established eukaryotic binding models.
- Regulatory genomics enrichment analysis
- Assess whether sets of genomic regions—such as experimental peak calls or differentially accessible chromatin—are significantly enriched for specific transcription factor motifs.
- Automated data integration via API
- Retrieve position frequency matrices and metadata programmatically into custom bioinformatics pipelines using the RESTful API or pyJASPAR.
Query it here
The research agent queries JASPAR directly — no account, no API key — and every answer links back to the record it came from. Ask in plain language and it writes the query.
Strengths and limits
Good at
- Provides manually curated, non-redundant binding profiles backed by experimental evidence.
- Covers a broad taxonomic breadth spanning vertebrates, insects, plants, nematodes, fungi, and urochordates.
- Supports multiple motif representations, including standard PFMs, PWMs, and flexible TFFMs.
- Offers programmatic access via a dedicated RESTful API and Python library alongside batch downloads.
Watch out for
- Does not inherently supply binding models for all transcription factors, separating non-curated data into unvalidated collections.
- Focuses on eukaryotic organisms and excludes prokaryotic regulatory models.
Questions
Can I search JASPAR without writing code?
Yes. The research agent queries JASPAR directly, with no account or API key, and cites the record behind every answer. Ask in plain language — for a gene, a protein, a compound or a study — and it builds the query for you.
Can I reuse data from JASPAR?
CC BY 4.0. Terms: https://jaspar.elixir.no/about/
What is the difference between JASPAR CORE and other collections?
JASPAR CORE contains only curated, non-redundant profiles derived from published collections of experimentally verified eukaryotic transcription factor binding sites. Other collections include unvalidated profiles and deep learning models.
In what formats can transcription factor binding profiles be accessed?
Profiles are stored as position frequency matrices (PFMs) and transcription factor flexible models (TFFMs). Users can derive position-specific weight matrices (PWMs) directly from the supplied PFMs.
How can researchers query JASPAR programmatically?
JASPAR provides a dedicated RESTful API for programmatic requests, as well as the pyJASPAR Python package for integration within Python data science workflows.
How to cite it
Baydar Ovek D, Rauluseviciute I, Aronsen DR, Blanc-Mathieu R, Bonthuis I, de Beukelaer H, Ferenc K, Jegou A, Kumar V, Lemma RB, Lucas J, Pochon M, Yun CM, Ramalingam V, Deshpande SS, Patel A, Marinov GK, Wang AT, Aguirre A, Castro-Mondragon JA, Baranasic D, Chèneby J, Gundersen S, Johansen M, Khan A, Kuijjer ML, Hovig E, Lenhard B, Sandelin A, Vandepoele K, Wasserman WW, Parcy F, Kundaje A, Mathelier A. JASPAR 2026: expansion of transcription factor binding profiles and integration of deep learning models. Nucleic Acids Res. 2026 Jan 6;54(D1):D184-D193.; doi: 10.1093/nar/gkaf1209
Written from JASPAR's own website and reference material. Statements citing a figure that does not appear there are removed before publication. Licence and running details come from our registry.