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Super-enhancers in the control of cell identity and disease

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Mutation of sequences flanking and separating transcription factor binding sites in a Drosophila enhancer significantly alter its outputPreprint

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Deciphering the regulatory logic of a Drosophila enhancer through systematic sequence mutagenesis and quantitative image analysisPreprint

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Predicting the impact of sequence motifs on gene regulation using single-cell dataPreprint

Hepkema, J., Lee, N. K., Stewart, B. J., Ruangroengkulrith, S., Charoensawan, V., Clatworthy, M. R., & Hemberg, M. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.11.26.400218 · Cited by 2

Quantifying the contribution of DNA conformational flexibility to transcription factor binding on nucleosomal DNA uncovers indirect readout across diverse TF familiesPreprint

Dey, U., Martinez, G. S., Kumar, R., Yella, V. R., & Kumar, A. A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.21.655105 · Cited by 2

An automated ATAC-seq method reveals sequence determinants of transcription factor dose response in the open chromatinPreprint

Liu, B. B., Shimasawa, M., Vermeulen, S. Y., Kim, S. H., Iremadze, N., Lipson, D., Shipony, Z., & Greenleaf, W. J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.24.666684 · Cited by 2

Genetic and epigenetic control of life cycle transitions in the brown alga Ectocarpus sp.

Bourdareau, S. (2018) · theses.fr (ABES) · doi:10.70675/78884081zb539z4200z8bd7zc2774b41cca6 · Cited by 3

Why the c‐Fos/c‐Jun complex is extremely conserved: An in vitro evolution exploration by combining cDNA display and proximity ligation

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Crosstalk between chromatin and Shavenbaby defines transcriptional output along the Drosophila intestinal stem cell lineage

Mancheno-Ferris, A., Immarigeon, C., Rivero, A., Depierre, D., Schickele, N., Fosseprez, O., Chanard, N., Aughey, G., Lhoumaud, P., Anglade, J., et al. (2023) · iScience · doi:10.1016/j.isci.2023.108624 · Cited by 1

Position Weight Matrix or Acyclic Probabilistic Finite Automaton: Which model to use? A decision rule inferred for the prediction of transcription factor binding sites

Lavezzo, G. M., Lauretto, M. D. S., Andrioli, L. P. M., & Machado‐Lima, A. (2023) · Genetics and Molecular Biology · doi:10.1590/1678-4685-gmb-2023-0048 · Cited by 1

DNA-Binding Activities of KSHV DNA Polymerase Processivity Factor (PF-8) Complexes

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Structural basis for higher-order DNA binding by a bacterial transcriptional regulator

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Genes, DNA, and Protein–DNA Interactions

Roy, S. (2025) · Springer eBooks · doi:10.1007/978-981-96-6823-6_1 · Cited by 1

A Deep Learning Framework with Multi-perspective Feature Fusion for Transcription Factor Binding Site Prediction

Wang, T., & Liu, Z. (2026) · Interdisciplinary Sciences Computational Life Sciences · doi:10.1007/s12539-025-00807-2 · Cited by 1

From the Beauty of Genomic Landscapes to the Strength of Transcriptional Mechanisms

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Single-cell TF-DNA binding prediction and analysis based on transfer learning framework

Wang, Z., Zhang, Y., Yu, Y., Wang, M., Liu, Y., & Zou, Q. (2022) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm55620.2022.9995189 · Cited by 1

Using Synthetic DNA Libraries to Investigate Chromatin and Gene Regulation

Kleinschmidt, H., Xu, C., & Bai, L. (2023) · Chromosoma · doi:10.1007/s00412-023-00796-5 · Cited by 2

Short, but matters: short tandem repeats confer variation in transcription factor-DNA binding

Zhang, J., & Zhu, B. (2023) · 中国科学通报：英文版 · doi:10.1016/j.scib.2023.11.050 · Cited by 1

Reader-Effectors as Actuators of Epigenome Editing

Kim, S. H., & Haynes, K. A. (2024) · Methods in molecular biology · doi:10.1007/978-1-0716-4051-7_5 · Cited by 1

In need of good neighbours: transcription factors require local DNA hypomethylation for target binding

Karemaker, I. D., & Vermeulen, M. (2016) · The EMBO Journal · doi:10.15252/embj.201593750 · Cited by 1

DNA minor groove electrostatic potential: influence of sequence-specific transitions of the torsion angle gamma and deoxyribose conformations

Zhitnikova, M. Y., & Shestopalova, A. V. (2016) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2016.1255259 · Cited by 1

Challenges with modelling transcription factor binding

Machanick, P., & Kibet, C. K. (2017) · International Conference on Next Generation Computing Applications (NextComp) · doi:10.1109/nextcomp.2017.8016178 · Cited by 1

Phylogenetic Manifold Regularization: A semi-supervised approach to predict transcription factor binding sites

Ahsan, F., Drouin, A., Laviolette, F., Precup, D., & Blanchette, M. (2020) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm49941.2020.9313437 · Cited by 1

General Designs Reveal a Purine-Pyrimidine Structural Code in Human DNA

Cohen, D. R. (2022) · Mathematics · doi:10.3390/math10152723 · Cited by 1

Intra-Domain Residue Coevolution in Transcription Factors Contributes to DNA Binding Specificity

Luan, Y., Tang, Z., He, Y., & Xie, Z. (2023) · Microbiology Spectrum · doi:10.1128/spectrum.03651-22 · Cited by 1

Conservation Genetics and Epigenetics of Pronghorn, Antilocapra americana

Hahn, E. E. (2016) · UA Campus Repository (The University of Arizona) · Cited by 1

Functional Interpretation of Genetic Variants Using Deep Learning Predicts Impact on EpigenomePreprint

Hoffman, G. E., Schadt, E. E., & Roussos, P. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/389056 · Cited by 1

Satb1integrates DNA sequence,shape, motif densityand torsional stressto differentially bind targets in nucleosome-dense regionsPreprint

Ghosh, R. P., Shi, Q., Yang, L., Reddick, M. P., Tv, N., Zhurkin, V. B., Fordyce, P. M., Stasevich, T. J., Chang, H. Y., Greenleaf, W. J., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/450262 · Cited by 1

Characterizing the epigenetic landscape of cellular populations from bulk and single-cell ATAC-seq informationPreprint

Gabitto, M. I., Rasmussen, A. W., Wapinski, O. L., Allaway, K. C., Carriero, N. J., Fishell, G., & Bonneau, R. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/567669 · Cited by 1

DNA methylation-dependent and -independent binding of CDX2 directs activation of distinct developmental and homeostatic genesPreprint

Lorzadeh, A., Ye, G., Sharma, S., & Jadhav, U. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.11.579850 · Cited by 1

The Regulatory Logic of Planarian Stem Cell DifferentiationPreprint

Pérez-Posada, A., García-Castro, H., Emili, E., Vanni, V., Arias-Baldrich, C., Frölich, S., van Heeringen, S. J., Kenny, N. J., & Solana, J. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.23.608747 · Cited by 1

Benchmarking PWM and SVM-based Models for Transcription Factor Binding Site Prediction: A Comparative Analysis on Synthetic and Biological DataPreprint

Tognon, M., Kumbara, A., Betti, A., Ruggeri, L., & Giugno, R. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.03.20.644354 · Cited by 1

Binning-based Methods for Model Fitting and Data Splitting Improve Machine Learning Imbalanced RegressionPreprint

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Structured Data Modeling with Deep Kernel Machines and Applications in Computational Biology

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Essential genes are dominantly activated by single transcription factorsPreprint

Capriati, M., Nestmann, S., Akan, I. S., Tuschmann, F., Druffel‐Augustin, S., & Grand, R. S. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.04.27.721063 · Cited by 2

Dual codon usage in germline variants of prostate cancer genomes

Kuznetsova, I. L. (2015) · Tampere University Institutional Repository (Tampere University)

Lessons from viruses: Small non‐coding RNA meets transcription factors (comment on DOI 10.1002/bies.201500060)

Cavaillé, J. (2015) · BioEssays · doi:10.1002/bies.201500092

Non Parametric Unsupervised Clustering of ChIP Enrichment Regions Provides Isolation Vectors for Differential Functional Analysis

Griffith, A. (2016) · uO Research (University of Ottawa) · doi:10.20381/ruor-849

Discriminative Motif Elicitation via Maximization of Statistical Overpresentation

Li, N. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-63309-1_45

MADS evolution : insights into evolutionary changes in transcription factors and their binding sites

de Bruijn, S.-A. (2017) · doi:10.18174/421346

A Generalized Biophysical Model of Transcription Factor Binding Specificity and Its Application on High-Throughput SELEX Data

Ruan, S. (2017) · Open Scholarship Institutional Repository (Washington University in St. Louis) · doi:10.7936/k7fx78w6

Decipher Mechanisms by which Nuclear Respiratory Factor One (NRF1) Coordinates Changes in the Transcriptional and Chromatin Landscape Affecting Development and Progression of Invasive Breast Cancer

Ramos, J. D. (2018) · doi:10.25148/etd.fidc007034

DNA shape complements sequence-based representations of transcription factor binding sitesPreprint

DeFord, P., & Taylor, J. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/666735

Context-dependent gene regulation by transcription factor complexesPreprint

Kribelbauer-Swietek, J. F., Loker, R., Feng, S., Rastogi, C., Abe, N., Rube, H. T., Bussemaker, H. J., & Mann, R. S. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/706473

The Non-continuum Nature of Eukaryotic Transcriptional Regulation

Poon, G. M. K. (2021) · Advances in experimental medicine and biology · doi:10.1007/5584_2021_618

Predicting functional elements and variants effects in non-coding regions based on deep learning

Liu, Y., Peng, S., Shu, W., Jiang, B., Yang, C., & Xie, K. (2021) · IEEE International Conference on e-Health Networking, Applications and Services (Healthcom) · doi:10.1109/healthcom49281.2021.9398970

On exploring effects of coevolving residues on DNA binding specificity of transcription factorsPreprint

Luan, Y., & Xie, Z. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.20.445059

Structural and functional characterisation of FOXP1 and FOXP2 near-full length variants and their protein-protein interactions

Thulo, M. (2019)

Prediction of Transcription Factor Binding Sites Using Deep Learning Combined with DNA Sequences and Shape Feature Data

Li, Y., Liu, J., & Liu, H. (2021) · ACM International Conference on Multimedia in Asia (MMAsia) · doi:10.1145/3469877.3497696

Caracterização estrutural do polimorfismo -964G<A na interação do fator de transcrição HIF1 com seu elemento regulatório na região promotora do gene HLA-G

Alves, C. C. (2021) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/t.17.2021.tde-05112021-105440

Vorhersage, Analyse und Bedeutung charakteristischer Transkriptionsfaktor-Bindestellen und deren potentielle Masterkontrollfunktion in der transkriptionellen Genregulation

Haubrock, M. (2021) · doi:10.53846/goediss-8880

Discovery and prediction of protein binding sites in DNA and RNA sequences using Bayesian Markov models

Ge, W. (2021) · doi:10.53846/goediss-8555

Faculty Opinions recommendation of Enhancer Features that Drive Formation of Transcriptional Condensates.

Chang, C. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.736380697.793564443

Faculty Opinions recommendation of Proneural factors Ascl1 and Neurog2 contribute to neuronal subtype identities by establishing distinct chromatin landscapes.

Brüstle, O. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.735751490.793564377

Prediction of mammalian tissue-specific CLOCK-BMAL1 binding to E-box motifsPreprint

Marri, D., Filipovic, D., Kana, O. Z., Tischkau, S., & Bhattacharya, S. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.27.497767

Crosstalk between chromatin and the transcription factor Shavenbaby defines transcriptional output along the Drosophila intestinal stem cell lineagePreprint

Mancheno-Ferris, A., Immarigeon, C., Rivero, A., Depierre, D., Chanard, N., Fosseprez, O., Aughey, G., Lhoumaud, P., Anglade, J., Southall, T. D., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.01.03.522588

Measuring the impact of chromatin context on transcription factor binding affinities

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Accessibility and activity of transcriptional regulatory elements during sea urchin embryogenesis and differentiationPreprint

Arenas‐Mena, C., & Akin, S. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.05.14.540718

Assessing NGS-based computational methods for predicting transcriptional regulators with query gene setsPreprint

Lu, Z., Xiao, X., Zheng, Q., Wang, X., & Xu, L. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.02.01.578316

Transcription Factor Binding Site Detector Neural Networks trained with Various DNA Representations

Pap, G. (2023) · doi:10.14232/phd.11767

Context dependent activity of p63-bound gene regulatory elementsPreprint

McCann, A. A., Baniulyte, G., Woodstock, D. L., & Sammons, M. A. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.05.09.593326

Exploring Protein-DNA Binding Residue Prediction and Consistent Interpretability Analysis Using Deep LearningPreprint

Liu, Y. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.10.12.613667

A DNA base-specific sequence interposed between CRX and NRL contributes to RHODOPSIN expression

Maritato, R., Medugno, A., D’Andretta, E., Riso, G. D., Lupo, M., Botta, S., Marrocco, E., Renda, M., Sofia, M., Mussolino, C., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-76664-8

DNA-binding domain-aware classification enables systematic annotation of the regulatory genomePreprint

Ickes, C., Timucin, C. H., Harms, B. C., Akgül, U., Vicente-Hernández, Í., Bogeski, I., Beißbarth, T., & Haubrock, M. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.20.629625

How to Find Targets That Are Always Hidden: Nucleosome-Covered DNA and Pioneer Transcription Factors

Mondal, A. K., & Kolomeisky, A. B. (2024) · Springer eBooks · doi:10.1007/978-3-031-67802-8_23

Electrical Forces Improve Memory in Old Age

McCaig, C. (2025) · Reviews of physiology, biochemistry and pharmacology · doi:10.1007/978-3-031-68827-0_21

Learning interpretable representation for context-specific transcription regulatory networks using a foundation modelPreprint

Yu, Z., Yang, D., Chen, Q., Zhang, Y., Li, Z., Wang, Y., Wang, C., & Zhang, Y. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.03.29.646077

Decoding the Central Dogma: Quantitative Insights into Transcription and Translation Dynamics in the P53-Mediated DNA Damage ResponsePreprint

Lahav, G., François, J., & Jambhekar, A. (2025) · SSRN Electronic Journal · doi:10.2139/ssrn.5210934

Non-consensus flanking sequence of hundreds of base pairs around in vivo binding sites: statistical beacons for transcription factor scanningPreprint

Faltejsková, K., Šulc, J., & Vondrášek, J. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.28.656598

DeepCatl: A Combination of Channel Attention Mechanism and Transformer Encoding to Predict Transcription Factor Binding Sites

Wang, W., Zheng, Z., Wu, G., & Wang, X. (2025) · Lecture notes in computer science · doi:10.1007/978-981-95-0030-7_41

DNA Conformational Flexibility Descriptors Improve Transcription Factor Binding Prediction Across the Protein FamiliesPreprint

Dey, U., Yella, V. R., & Kumar, A. A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.20.665724

Conservation of chromatin states and their association with transcription factors in land plantsPreprint

Shukla, V., Axelsson, E., Hisanaga, T., Haseloff, J. P., Berger, F., & Romani, F. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.12.664529

The emerging sequence grammar of 3D genome organisation

Tamon, L., Ashford, J., Nicholls, M., Bruijn, M. F. T. R. D., & Sahakyan, A. B. (2025) · Human Genetics · doi:10.1007/s00439-025-02772-8

Scalable transcription factor mapping uncovers the regulatory dynamics of natural and synthetic transcription factors in human T cell statesPreprint

Mullins, R. D. Z., Zaretsky, J. M., Stoller, E., Moore, M., Takacsi-Nagy, O., Shpynov, O., Sampaleanu, R., Roth, T. L., Satpathy, A. T., Mitra, R. D., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.10.09.681414

Oyster: A Neural Network for Modeling Genomic Sequences with Exact Position-Specific k -mer ContributionsPreprint

Abdulnabi, H., & Westwood, J. T. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.11.01.686014 · Cited by 1

Challenges in predicting chromatin accessibility differences between species

Stephen, A. Z. M., Raje, A., Sestili, H. H., Wirthlin, M. E., Lawler, A. J., Brown, A. R., Ma, J., Stauffer, W. R., Pfenning, A. R., & Kaplow, I. M. (2026) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqag059

The heat shock transcription factor regulates the expression of crustin in Portunus trituberculatus

Wu, Y., Zhang, Y., Zheng, J., & Cui, Z. (2025) · Fish & Shellfish Immunology · doi:10.1016/j.fsi.2025.111020

Linking hierarchical classification of transcription factors by the structure of their DNA-binding domains to the variability of their binding site motifs

Levitsky, V. G., Vatolina, T. Y., & Raditsa, V. V. (2025) · Vavilov Journal of Genetics and Breeding · doi:10.18699/vjgb-25-99

Additional file 7 of G-quadruplexes are transcription factor binding hubs in human chromatin

Spiegel, J., Cuesta, S. M., Adhikari, S., Hänsel‐Hertsch, R., Tannahill, D., & Balasubramanian, S. (2021) · Figshare · doi:10.6084/m9.figshare.14478437

Additional file 11 of Comparative transcriptomic analysis of races 1, 2, 5 and 6 of Fusarium oxysporum f.sp. pisi in a susceptible pea host identifies differential pathogenicity profiles

Achari, S. R., Edwards, J., Mann, R. C., Kaur, J., Sawbridge, T., & Summerell, B. A. (2021) · Figshare · doi:10.6084/m9.figshare.16779355

Additional file 4 of Systematic identification of non-canonical transcription factor motifs

Chumpitaz-Diaz, L., Samee, M. A. H., & Pollard, K. S. (2021) · Figshare · doi:10.6084/m9.figshare.16551042

Additional file 5 of Systematic identification of non-canonical transcription factor motifs

Chumpitaz-Diaz, L., Samee, M. A. H., & Pollard, K. S. (2021) · Figshare · doi:10.6084/m9.figshare.16551045

Additional file 6 of Comparative transcriptomic analysis of races 1, 2, 5 and 6 of Fusarium oxysporum f.sp. pisi in a susceptible pea host identifies differential pathogenicity profiles

Achari, S. R., Edwards, J., Mann, R. C., Kaur, J., Sawbridge, T., & Summerell, B. A. (2021) · Figshare · doi:10.6084/m9.figshare.16779394

Additional file 6 of Systematic identification of non-canonical transcription factor motifs

Chumpitaz-Diaz, L., Samee, M. A. H., & Pollard, K. S. (2021) · Figshare · doi:10.6084/m9.figshare.16551048

Additional file 2 of Comparative transcriptomic analysis of races 1, 2, 5 and 6 of Fusarium oxysporum f.sp. pisi in a susceptible pea host identifies differential pathogenicity profiles

Achari, S. R., Edwards, J., Mann, R. C., Kaur, J., Sawbridge, T., & Summerell, B. A. (2021) · Figshare · doi:10.6084/m9.figshare.16779382

Additional file 9 of Comparative transcriptomic analysis of races 1, 2, 5 and 6 of Fusarium oxysporum f.sp. pisi in a susceptible pea host identifies differential pathogenicity profiles

Achari, S. R., Edwards, J., Mann, R. C., Kaur, J., Sawbridge, T., & Summerell, B. A. (2021) · Figshare · doi:10.6084/m9.figshare.16779403

Additional file 1 of Comparative transcriptomic analysis of races 1, 2, 5 and 6 of Fusarium oxysporum f.sp. pisi in a susceptible pea host identifies differential pathogenicity profiles

Achari, S. R., Edwards, J., Mann, R. C., Kaur, J., Sawbridge, T., & Summerell, B. A. (2021) · Figshare · doi:10.6084/m9.figshare.16779379

Additional file 2 of Predicting the impact of sequence motifs on gene regulation using single-cell data

Hepkema, J., Lee, N. K., Stewart, B. J., Ruangroengkulrith, S., Charoensawan, V., Clatworthy, M. R., & Hemberg, M. (2023) · Figshare · doi:10.6084/m9.figshare.23962000

Additional file 13 of Comparative transcriptomic analysis of races 1, 2, 5 and 6 of Fusarium oxysporum f.sp. pisi in a susceptible pea host identifies differential pathogenicity profiles

Achari, S. R., Edwards, J., Mann, R. C., Kaur, J., Sawbridge, T., & Summerell, B. A. (2021) · Figshare · doi:10.6084/m9.figshare.16779361

Additional file 1 of intePareto: an R package for integrative analyses of RNA-Seq and ChIP-Seq data

Cao, Y., Kitanovski, S., & Hoffmann, D. (2020) · Figshare · doi:10.6084/m9.figshare.13502190

Additional file 3 of Comparative transcriptomic analysis of races 1, 2, 5 and 6 of Fusarium oxysporum f.sp. pisi in a susceptible pea host identifies differential pathogenicity profiles

Achari, S. R., Edwards, J., Mann, R. C., Kaur, J., Sawbridge, T., & Summerell, B. A. (2021) · Figshare · doi:10.6084/m9.figshare.16779385

Additional file 5 of Comparative transcriptomic analysis of races 1, 2, 5 and 6 of Fusarium oxysporum f.sp. pisi in a susceptible pea host identifies differential pathogenicity profiles

Achari, S. R., Edwards, J., Mann, R. C., Kaur, J., Sawbridge, T., & Summerell, B. A. (2021) · Figshare · doi:10.6084/m9.figshare.16779391

Additional file 10 of Comparative transcriptomic analysis of races 1, 2, 5 and 6 of Fusarium oxysporum f.sp. pisi in a susceptible pea host identifies differential pathogenicity profiles

Achari, S. R., Edwards, J., Mann, R. C., Kaur, J., Sawbridge, T., & Summerell, B. A. (2021) · Figshare · doi:10.6084/m9.figshare.16779352

Additional file 12 of Comparative transcriptomic analysis of races 1, 2, 5 and 6 of Fusarium oxysporum f.sp. pisi in a susceptible pea host identifies differential pathogenicity profiles

Achari, S. R., Edwards, J., Mann, R. C., Kaur, J., Sawbridge, T., & Summerell, B. A. (2021) · Figshare · doi:10.6084/m9.figshare.16779358

Additional file 4 of Comparative transcriptomic analysis of races 1, 2, 5 and 6 of Fusarium oxysporum f.sp. pisi in a susceptible pea host identifies differential pathogenicity profiles

Achari, S. R., Edwards, J., Mann, R. C., Kaur, J., Sawbridge, T., & Summerell, B. A. (2021) · Figshare · doi:10.6084/m9.figshare.16779388

Additional file 1 of An interpretable bimodal neural network characterizes the sequence and preexisting chromatin predictors of induced transcription factor binding

Srivastava, D., Aydın, B., Mazzoni, E. O., & Mahony, S. (2021) · Figshare · doi:10.6084/m9.figshare.13544596

Additional file 3 of Predicting the impact of sequence motifs on gene regulation using single-cell data

Hepkema, J., Lee, N. K., Stewart, B. J., Ruangroengkulrith, S., Charoensawan, V., Clatworthy, M. R., & Hemberg, M. (2023) · Figshare · doi:10.6084/m9.figshare.23962003

Additional file 1 of Predicting the impact of sequence motifs on gene regulation using single-cell data

Hepkema, J., Lee, N. K., Stewart, B. J., Ruangroengkulrith, S., Charoensawan, V., Clatworthy, M. R., & Hemberg, M. (2023) · Figshare · doi:10.6084/m9.figshare.23961997

Additional file 9 of G-quadruplexes are transcription factor binding hubs in human chromatin

Spiegel, J., Cuesta, S. M., Adhikari, S., Hänsel‐Hertsch, R., Tannahill, D., & Balasubramanian, S. (2021) · Figshare · doi:10.6084/m9.figshare.14478443

Additional file 1 of G-quadruplexes are transcription factor binding hubs in human chromatin

Spiegel, J., Cuesta, S. M., Adhikari, S., Hänsel‐Hertsch, R., Tannahill, D., & Balasubramanian, S. (2021) · Figshare · doi:10.6084/m9.figshare.14478419

Additional file 3 of An interpretable bimodal neural network characterizes the sequence and preexisting chromatin predictors of induced transcription factor binding

Srivastava, D., Aydın, B., Mazzoni, E. O., & Mahony, S. (2021) · Figshare · doi:10.6084/m9.figshare.13544602

Transcription factor–DNA binding: beyond binding site motifs

Inukai, S., Kock, K. H., & Bulyk, M. L. (2017) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2017.02.007 · Cited by 387

14 Quantitative modeling of transcription factor binding specificities using DNA shape

Zhou, T., Shen, N., Yang, L., Abe, N., Horton, J., Mann, R. S., Bussemaker, H. J., Gordân, R., & Rohs, R. (2015) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2015.1032554 · Cited by 6

Genetic Variation in Transcription Factor Binding Sites

Santpere, G. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24055038 · Cited by 5

Proteins Recognizing DNA: Structural Uniqueness and Versatility of DNA-Binding Domains in Stem Cell Transcription Factors

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Mechanisms of transcription factor selectivity

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