JASPAR 2026 : expansion of transcription factor binding profiles and integration of deep learning models
- Author
- Damla Ovek Baydar, Ieva Rauluseviciute, Dina R Aronsen, Romain Blanc-Mathieu, Ine Bonthuis, Herman De Beukelaer (UGent) , Katalin Ferenc, Alice Jegou, Vipin Kumar, Roza Berhanu Lemma, Jérémy Lucas, Mathis Pochon, Chang M Yun, Vivekanandan Ramalingam, Salil Sanjay Deshpande, Aman Patel, Georgi K Marinov, Austin T Wang, Alejandro Aguirre, Jaime A Castro-Mondragon, Damir Baranasic, Jeanne Chèneby, Sveinung Gundersen, Morten Johansen, Aziz Khan, Marieke L Kuijjer, Eivind Hovig, Boris Lenhard, Albin Sandelin, Klaas Vandepoele (UGent) , Wyeth W Wasserman, François Parcy, Anshul Kundaje and Anthony Mathelier
- Organization
- Abstract
- JASPAR (https://jaspar.elixir.no/) is an open-access database that has provided high-quality, manually curated, and non-redundant DNA binding profiles for transcription factors (TFs) as position frequency matrices (PFMs) for over 20 years. We expanded the CORE (306 new profiles, 12% increase) and UNVALIDATED (433, 60% increase) collections with new PFMs and updated 13 existing profiles. We updated the TF binding site predictions and genome tracks for eight species. TF binding profile clusters and familial TF binding sites were updated accordingly. We integrate the inMOTIFin software to easily simulate regulatory sequences using JASPAR PFMs. To enrich TFs' annotations, we provide scientific literature-based human TF target information. Notably, this release features a deep learning (DL) collection, providing a paradigm shift in modeling and characterizing TF-DNA interactions with 1259 BPNet models trained on Homo sapiens ENCODE chromatin immunoprecipitation followed by sequencing (ChIP-seq) datasets from 240 TFs and interpreted to reveal predictive motif patterns for the models. The motifs associated with the same TF were clustered to provide a summary of the binding properties, resulting in 240 primary and 113 alternative motif patterns in the DL collection. The JASPAR 2026 collections lay a foundation for future endeavors in genomic research, serving the scientific community in uncovering the mechanisms of gene regulation.
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Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01KCR2W98RKWQSDXDWRDBJ9NN3
- MLA
- Ovek Baydar, Damla, et al. “JASPAR 2026 : Expansion of Transcription Factor Binding Profiles and Integration of Deep Learning Models.” NUCLEIC ACIDS RESEARCH, vol. 54, no. D1, 2026, pp. D184–93, doi:10.1093/nar/gkaf1209.
- APA
- Ovek Baydar, D., Rauluseviciute, I., Aronsen, D. R., Blanc-Mathieu, R., Bonthuis, I., De Beukelaer, H., … Mathelier, A. (2026). JASPAR 2026 : expansion of transcription factor binding profiles and integration of deep learning models. NUCLEIC ACIDS RESEARCH, 54(D1), D184–D193. https://doi.org/10.1093/nar/gkaf1209
- Chicago author-date
- Ovek Baydar, Damla, Ieva Rauluseviciute, Dina R Aronsen, Romain Blanc-Mathieu, Ine Bonthuis, Herman De Beukelaer, Katalin Ferenc, et al. 2026. “JASPAR 2026 : Expansion of Transcription Factor Binding Profiles and Integration of Deep Learning Models.” NUCLEIC ACIDS RESEARCH 54 (D1): D184–93. https://doi.org/10.1093/nar/gkaf1209.
- Chicago author-date (all authors)
- Ovek Baydar, Damla, Ieva Rauluseviciute, Dina R Aronsen, Romain Blanc-Mathieu, Ine Bonthuis, Herman De Beukelaer, Katalin Ferenc, Alice Jegou, Vipin Kumar, Roza Berhanu Lemma, Jérémy Lucas, Mathis Pochon, Chang M Yun, Vivekanandan Ramalingam, Salil Sanjay Deshpande, Aman Patel, Georgi K Marinov, Austin T Wang, Alejandro Aguirre, Jaime A Castro-Mondragon, Damir Baranasic, Jeanne Chèneby, Sveinung Gundersen, Morten Johansen, Aziz Khan, Marieke L Kuijjer, Eivind Hovig, Boris Lenhard, Albin Sandelin, Klaas Vandepoele, Wyeth W Wasserman, François Parcy, Anshul Kundaje, and Anthony Mathelier. 2026. “JASPAR 2026 : Expansion of Transcription Factor Binding Profiles and Integration of Deep Learning Models.” NUCLEIC ACIDS RESEARCH 54 (D1): D184–D193. doi:10.1093/nar/gkaf1209.
- Vancouver
- 1.Ovek Baydar D, Rauluseviciute I, Aronsen DR, Blanc-Mathieu R, Bonthuis I, De Beukelaer H, et al. JASPAR 2026 : expansion of transcription factor binding profiles and integration of deep learning models. NUCLEIC ACIDS RESEARCH. 2026;54(D1):D184–93.
- IEEE
- [1]D. Ovek Baydar et al., “JASPAR 2026 : expansion of transcription factor binding profiles and integration of deep learning models,” NUCLEIC ACIDS RESEARCH, vol. 54, no. D1, pp. D184–D193, 2026.
@article{01KCR2W98RKWQSDXDWRDBJ9NN3,
abstract = {{JASPAR (https://jaspar.elixir.no/) is an open-access database that has provided high-quality, manually curated, and non-redundant DNA binding profiles for transcription factors (TFs) as position frequency matrices (PFMs) for over 20 years. We expanded the CORE (306 new profiles, 12% increase) and UNVALIDATED (433, 60% increase) collections with new PFMs and updated 13 existing profiles. We updated the TF binding site predictions and genome tracks for eight species. TF binding profile clusters and familial TF binding sites were updated accordingly. We integrate the inMOTIFin software to easily simulate regulatory sequences using JASPAR PFMs. To enrich TFs' annotations, we provide scientific literature-based human TF target information. Notably, this release features a deep learning (DL) collection, providing a paradigm shift in modeling and characterizing TF-DNA interactions with 1259 BPNet models trained on Homo sapiens ENCODE chromatin immunoprecipitation followed by sequencing (ChIP-seq) datasets from 240 TFs and interpreted to reveal predictive motif patterns for the models. The motifs associated with the same TF were clustered to provide a summary of the binding properties, resulting in 240 primary and 113 alternative motif patterns in the DL collection. The JASPAR 2026 collections lay a foundation for future endeavors in genomic research, serving the scientific community in uncovering the mechanisms of gene regulation.}},
author = {{Ovek Baydar, Damla and Rauluseviciute, Ieva and Aronsen, Dina R and Blanc-Mathieu, Romain and Bonthuis, Ine and De Beukelaer, Herman and Ferenc, Katalin and Jegou, Alice and Kumar, Vipin and Lemma, Roza Berhanu and Lucas, Jérémy and Pochon, Mathis and Yun, Chang M and Ramalingam, Vivekanandan and Deshpande, Salil Sanjay and Patel, Aman and Marinov, Georgi K and Wang, Austin T and Aguirre, Alejandro and Castro-Mondragon, Jaime A and Baranasic, Damir and Chèneby, Jeanne and Gundersen, Sveinung and Johansen, Morten and Khan, Aziz and Kuijjer, Marieke L and Hovig, Eivind and Lenhard, Boris and Sandelin, Albin and Vandepoele, Klaas and Wasserman, Wyeth W and Parcy, François and Kundaje, Anshul and Mathelier, Anthony}},
issn = {{0305-1048}},
journal = {{NUCLEIC ACIDS RESEARCH}},
keywords = {{MOUSE}},
language = {{eng}},
number = {{D1}},
pages = {{D184--D193}},
title = {{JASPAR 2026 : expansion of transcription factor binding profiles and integration of deep learning models}},
url = {{http://doi.org/10.1093/nar/gkaf1209}},
volume = {{54}},
year = {{2026}},
}
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