The DOI matches its Crossref record; 124 of the 124 references it cites were found in a registry or an index.
Dynamic regulation of transcriptional states by chromatin and transcription factors
Open accessAbstract
The interaction of regulatory proteins with the complex nucleoprotein structures that are found in mammalian cells involves chromatin reorganization at multiple levels. Mechanisms that support these transitions are complex on many timescales, which range from milliseconds to minutes or hours. In this Review, we discuss emerging concepts regarding the function of regulatory elements in living cells. We also explore the involvement of these dynamic and stochastic processes in the evolution of fluctuating transcriptional activity states that are now commonly reported in eukaryotic systems.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“As a transcription factor, the GR interacts with and influences the histone landscape, playing a critical role in shaping it.124,125”
From Epigenetic regulation in major depression and other stress-related disorders: molecular mechanisms, clinical relevance and therapeutic potential (2023) · cites this paper as [125]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In contrast to the long-held view, an accumulating body of work suggests that TFs do not bind DNA for periods of time longer than a few seconds26, 27.”
From Synergistic gene expression during the acute phase response is characterized by transcription factor assisted loading (2017) · cites this paper as [26]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“While it is clear that enhancers typically favour the more flexible models of sequence organisation, the degree of necessary cooperation between TFs is less obvious, particularly since TF binding to DNA appears to be very transient [113–117].”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [114]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Stochastic Gene Expression in a Single Cell
Elowitz, M. B., Levine, A. J., Siggia, E. D., & Swain, P. S. (2002) · Science · doi:10.1126/science.1070919 · Cited by 5,441
Network motifs: theory and experimental approaches
Alon, U. (2007) · Nature Reviews Genetics · doi:10.1038/nrg2102 · Cited by 3,279
A decade of exploring the cancer epigenome—biological and translational implications
Baylin, S. B., & Jones, P. A. (2011) · Nature Reviews Cancer · doi:10.1038/nrc3130 · Cited by 2,871
The accessible chromatin landscape of the human genome
Thurman, R. E., Rynes, E., Humbert, R., Vierstra, J., Maurano, M. T., Haugen, E., Sheffield, N. C., Stergachis, A. B., Wang, H., Vernot, B., et al. (2012) · Nature · doi:10.1038/nature11232 · Cited by 2,679
The biology of chromatin remodeling complexes.
Clapier, C. R., & Cairns, B. (2009) · Annual Review of Biochemistry · doi:10.1146/annurev.biochem.77.062706.153223 · Cited by 2,384
Stochasticity in gene expression: from theories to phenotypes
Kærn, M., Elston, T. C., Blake, W. J., & Collins, J. J. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1615 · Cited by 2,318
Transcription factors: from enhancer binding to developmental control
Spitz, F., & Furlong, E. E. M. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3207 · Cited by 2,227
Stability and flexibility of epigenetic gene regulation in mammalian development
Reik, W. (2007) · Nature · doi:10.1038/nature05918 · Cited by 1,963
Stochastic mRNA Synthesis in Mammalian Cells
Raj, A., Peskin, C. S., Tranchina, D., Vargas, D. Y., & Tyagi, S. (2006) · PLoS Biology · doi:10.1371/journal.pbio.0040309 · Cited by 1,737
Intrinsic and extrinsic contributions to stochasticity in gene expression
Swain, P. S., Elowitz, M. B., & Siggia, E. D. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.162041399 · Cited by 1,661
Flagged first, then by citations
Cited by
Sorted by citations
Items 301–400 of 495
Genome-Wide Mapping of In Vivo ERα–Binding Sites in Male Mouse Efferent Ductules
Yao, G., Hu, S., Yu, L., Ru, Y., Chen, C. D., Liu, Q., & Zhang, Y. (2017) · Endocrinology · doi:10.1210/en.2017-00483 · Cited by 9
Hunold, P., Pizzolato, G., Heramvand, N., Kaiser, L., Barbiera, G., van Ray, O., Thomas, R. K., George, J., Peifer, M., & Hänsel‐Hertsch, R. (2025) · Nature Communications · doi:10.1038/s41467-025-61797-9 · Cited by 8
Epigenetic priming as a driver of memory recall and dysfunction in T cells
Metzemaekers, M., Rinzema, N. J., & Stadhouders, R. (2025) · The Journal of Experimental Medicine · doi:10.1084/jem.20241433 · Cited by 8
Joining the PARty: PARP Regulation of KDM5A during DNA Repair (and Transcription?)
Sanchez, A. R., Buck‐Koehntop, B. A., & Miller, K. M. (2022) · BioEssays · doi:10.1002/bies.202200015 · Cited by 8
Wang, M., Ji, C., Zhang, Y., Zhang, Z., Zhang, Y., Guo, H., Qiao, N., Zhou, X., Cao, X., Ye, Z., et al. (2022) · Endocrine · doi:10.1007/s12020-022-03155-z · Cited by 8
Ma, M., Szavits-Nossan, J., Singh, A., & Grima, R. (2024) · Mathematical Biosciences · doi:10.1016/j.mbs.2024.109204 · Cited by 8
Lazar, M. A., & Birnbaum, M. J. (2016) · Elsevier eBooks · doi:10.1016/b978-0-323-29738-7.00003-4 · Cited by 8
Epigenomic regulation of OTU5 in Arabidopsis thaliana
Hsieh, J. A., Yen, M., & Chen, P. (2020) · Genomics · doi:10.1016/j.ygeno.2020.04.006 · Cited by 8
Interrogating cell type-specific cooperation of transcriptional regulators in 3D chromatin
Yi, X., Zheng, Z., Xu, H., Zhou, Y., Huang, D., Wang, J., Feng, X., Zhao, K., Fan, X., Zhang, S., et al. (2021) · iScience · doi:10.1016/j.isci.2021.103468 · Cited by 8
Smirnov, E., Hornáček, M., Vacı́k, T., Cmarko, D., & Raška, I. (2017) · Nucleus · doi:10.1080/19491034.2017.1419112 · Cited by 8
Lee, B. H., & Stallcup, M. R. (2018) · PLoS ONE · doi:10.1371/journal.pone.0196965 · Cited by 8
Stress Adaptation and the Hypothalamic‐Pituitary‐Adrenal Axis
Aguilera, G. (2016) · Wiley eBooks · doi:10.1002/9781118760369.ch17 · Cited by 8
Genome im Fokus: Entwicklung und Anwendungen von CRISPR‐Cas9‐Bildgebungstechnologien
Knight, S. C., Tjian, R., & Doudna, J. A. (2017) · Angewandte Chemie · doi:10.1002/ange.201709201 · Cited by 7
Regulatory Mechanisms for Transcriptional Bursting Revealed by an Event-Based Model
Wu, R., Zhou, B., Wang, W., & Liu, F. (2023) · Research · doi:10.34133/research.0253 · Cited by 8
Mega-enhancers compartmentalize transcriptionally active long genes in the brain
Zhao, Z., Parra, O. A. P., Fujita, S.-I., Musella, F., Alvarado, N. J. S., Alber, F., Yang, Y., & Yamada, T. (2026) · Nature Cell Biology · doi:10.1038/s41556-026-02043-2 · Cited by 7
Computational challenges in modeling gene regulatory events
Pataskar, A., & Tiwari, V. K. (2016) · Transcription · doi:10.1080/21541264.2016.1204491 · Cited by 7
Therapeutic potential of Mediator complex subunits in metabolic diseases
Ranjan, A., & Ansari, S. A. (2017) · Biochimie · doi:10.1016/j.biochi.2017.10.012 · Cited by 7
Noncoding Mutations in a Thyroid Hormone Receptor Gene That Impair Cone Photoreceptor Function
Liu, H., Lu, A., Kelley, K. A., & Forrest, D. (2023) · Endocrinology · doi:10.1210/endocr/bqad006 · Cited by 7
Transcriptional dynamics with time-dependent reaction rates
Nandi, S., & Ghosh, A. (2015) · Physical Biology · doi:10.1088/1478-3975/12/1/016015 · Cited by 7
Cerutti, C., Zhang, L., Tribollet, V., Shi, J., Brillet, R., Gillet, B., Hughes, S., Forcet, C., Shi, T., & Vanacker, J.-M. (2022) · Scientific Reports · doi:10.1038/s41598-022-07744-w · Cited by 8
Nimura, K., & Kaneda, Y. (2015) · Journal of Human Genetics · doi:10.1038/jhg.2015.84 · Cited by 7
NET-prism enables RNA polymerase-dedicated transcriptional interrogation at nucleotide resolution
Mylonas, C., & Tessarz, P. (2019) · RNA Biology · doi:10.1080/15476286.2019.1621625 · Cited by 7
Epigenetic modifications and the development of kidney graft fibrosis
Rousselle, T. V., Bardhi, E., Maluf, D. G., & Mas, V. R. (2020) · Current Opinion in Organ Transplantation · doi:10.1097/mot.0000000000000839 · Cited by 7
Profiling Protein–DNA Interactions by Chromatin Immunoprecipitation in Arabidopsis
Susila, H., Nasim, Z., Jin, S., Youn, G., Jeong, H., Jung, J., & Ahn, J. H. (2021) · Methods in molecular biology · doi:10.1007/978-1-0716-1186-9_21 · Cited by 7
Conserved HSFA1-dependent chromatin dynamics drive heat stress responses in plants
Yen, M.-J., Lin, K., Thalimaraw, L., Yang, H.-R., Boonyaves, K., Cheng, C.-Y., & Wu, T. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116714 · Cited by 6
Ward, C. J., Chakraborty, S., Shaji, S. K., Veiga-Villauriz, C., Al-Deka, A., Zhao, Q., Pramanik, J., Chen, X., & Mahata, B. (2026) · Cell Reports · doi:10.1016/j.celrep.2026.117367 · Cited by 6
Dynamic nucleosome landscape elicits a noncanonical GATA2 pioneer model
Li, T., Liu, Q., Chen, Z., Fang, K., Huang, F., Fu, X., Wang, Q., & Jin, V. X. (2022) · Nature Communications · doi:10.1038/s41467-022-30960-x · Cited by 6
Hu, L., Zhao, X., Li, P., Zeng, Y., Zhang, Y., Shen, Y., Wang, Y., Sun, X., Lai, B., & Zhong, C. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.864314 · Cited by 6
Dynamic modeling of the cellular senescence gene regulatory network
de Freitas, J. A. N. L. F., & Bischof, O. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e14007 · Cited by 7
Qin, W., Ren, Z., Xu, C., Cao, Y.-N., Sun, M., Huang, R., & Bao, W. (2023) · Cells · doi:10.3390/cells12060968 · Cited by 6
Kupkova, K., Shetty, S. J., Hoffman, E. A., Bekiranov, S., & Auble, D. (2024) · The EMBO Journal · doi:10.1038/s44318-024-00089-2 · Cited by 6
Vishnu, U. S., Estève, P., Chin, H. G., & Pradhan, S. (2021) · Epigenetics & Chromatin · doi:10.1186/s13072-021-00427-2 · Cited by 6
Barel, I., Naughton, B. S., Reich, N. O., & Brown, F. L. H. (2017) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.7b10349 · Cited by 6
Thyroid hormone dependent transcriptional programming by TRβ requires SWI/SNF chromatin remodelers
Gillis, N. E., Boyd, J. R., Tomczak, J. A., Frietze, S. E., & Carr, F. E. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab1287 · Cited by 7
Dynamic reprogramming of chromatin: paradigmatic palimpsests and HES factors
Kok, K., & Arnosti, D. N. (2015) · Frontiers in Genetics · doi:10.3389/fgene.2015.00029 · Cited by 6
GATA3 differentially regulates the transcriptome via zinc finger 2-modulated phase separation
Chen, Y., Wan, Y., Pei, X., Wei, Z., Wang, T., Zhang, J., & Chen, L. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115702 · Cited by 5
Lu, C., Guo, L., Fang, B., Shi, J., & Zhou, M. (2025) · Journal of Fungi · doi:10.3390/jof11040282 · Cited by 5
Stochastic multistationarity in a model of the hematopoietic stem cell differentiation network
Al-Radhawi, M. A., Kumar, N. S., Sontag, E. D., & Vecchio, D. D. (2018) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2018.8619300 · Cited by 6
Exogenous nucleosome-binding molecules: a potential new class of therapeutic drugs
Cabral, W. F., Machado, A. H. L., & Santos, G. M. (2016) · Drug Discovery Today · doi:10.1016/j.drudis.2016.01.017 · Cited by 5
Phosphorylation of ATF2 promotes odontoblastic differentiation via intrinsic HAT activity
Zuo, H., Xiao, Y., Han, J., Lin, Y., Tian, C., Zhang, S., Yuan, G., Liu, H., & Chen, Z. (2023) · Journal of genetics and genomics/Journal of Genetics and Genomics · doi:10.1016/j.jgg.2023.02.005 · Cited by 5
Role of Estrogen Response Element in the Human Prolactin Gene: Transcriptional Response and Timing
McNamara, A., Adamson, A. D., Dunham, L., Semprini, S., Spiller, D. G., McNeilly, A. S., Mullins, J. J., Davis, J. R., & White, M. (2015) · Molecular Endocrinology · doi:10.1210/me.2015-1186 · Cited by 5
Wang, X., Li, P., & Gutenkunst, R. N. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/138792 · Cited by 5
DNA accessibility is not the primary determinant of chromatin-mediated gene regulationPreprint
Chereji, R. V., Eriksson, P. R., Ocampo, J., & Clark, D. J. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/639971 · Cited by 5
Huang, Z., Luo, S., Wang, Z., Zhang, Z., Jiang, B., Nie, Q. H., & Zhang, J. (2024) · eLife · doi:10.7554/elife.100623 · Cited by 7
A toolkit for programmable transcriptional engineering across eukaryotic kingdomsPreprint
Ornelas, I. J., Owens, L. A., Álamos, S., Hummel, N. F. C., Zamora, M. G. H., Phan, N., Pattali, R. K., Shih, P. M., & Nuñez, J. K. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.10.705154 · Cited by 5
Combining phylogenetic footprinting with motif models incorporating intra-motif dependencies
Nettling, M., Treutler, H., Cerquides, J., & Große, I. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1495-1 · Cited by 4
Zandigohar, M., Rehman, J., & Dai, Y. D. (2025) · Bioinformatics · doi:10.1093/bioinformatics/btaf638 · Cited by 4
Tav, C., Fournier, É., Fournier, M., Khadangi, F., Baguette, A., Côté, M. C., Silveira, M. A. D., Bérubé‐Simard, F., Bourque, G., Droit, A., et al. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.1237092 · Cited by 4
Heo, Y., Kim, Y., Lim, W., Cho, H., Choi, Y. W., & Min, S. (2024) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2024.151010 · Cited by 4
Histone O-GlcNAcylation and Potential Biological Functions
Hirosawa, M., Hayakawa, K., Shiota, K., & Tanaka, S. (2018) · OBM Genetics · doi:10.21926/obm.genet.1803036 · Cited by 4
Linking dynamical complexities from activation signals to transcription responses
Lin, G., Jiao, F., Sun, Q., Tang, M., Yu, J., & Zhou, Z. (2019) · Royal Society Open Science · doi:10.1098/rsos.190286 · Cited by 4
Transcriptome Analysis and Intraspecific Variation in Spanish Fir (Abies pinsapo Boiss.)
Ortigosa, F., Ávila, C., Rubio, L., Garrido, L. Á., Carreira, J. A., Cañas, R. A., & Cánovas, F. M. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23169351 · Cited by 4
Synthetic enhancers including TFREs improve transgene expression in CHO cells
Liu, H.-N., Wang, X.-Y., Zou, Y., Wu, W.-B., Lin, Y., Ji, B.-Y., & Wang, T. (2024) · Heliyon · doi:10.1016/j.heliyon.2024.e26901 · Cited by 4
Bracken, R. C., Davison, L. M., Buehler, D. P., Fulton, M. E., Carson, E. E., Sheng, Q., Stolze, L. K., Guillermier, C., Steinhauser, M. L., & Brown, J. D. (2024) · iScience · doi:10.1016/j.isci.2024.110011 · Cited by 4
Integrative Approaches for Inference of Genome-Scale Gene Regulatory Networks
Siahpirani, A. F., Chasman, D. A., & Roy, S. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-8882-2_7 · Cited by 4
Chromatin Regulation and Transcription Factor Cooperation in Liver Cells
Goldstein, I. (2020) · Wiley eBooks · doi:10.1002/9781119436812.ch81 · Cited by 4
Liquid-like transcription condensates locally constrain chromatin in living human cellsPreprint
Semeigazin, A., Minami, K., Shimazoe, M. A., Khochbin, S., Panne, D., Ide, S., & Maeshima, K. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.05.663270 · Cited by 5
Genetic Basis of Familial Cancer Risk: A Narrative Review
Sabik, E. F. (2026) · DNA · doi:10.3390/dna6010005 · Cited by 3
Guo, W., Wang, Z., Xue, R., Zhang, X., Zhao, Q., Gao, Y., Wang, S., & Mao, Y. (2025) · Biomaterials · doi:10.1016/j.biomaterials.2025.123459 · Cited by 3
Manipulation of the nucleoscaffold potentiates cellular reprogramming kinetics
Yang, B. A., Vesga-Castro, C., da Rocha, A. M., Newton, I., Shcherbina, A., Wong, S. W., Fraczek, P. M., Larouche, J. A., Hiraki, H. L., Baker, B. M., et al. (2025) · PNAS Nexus · doi:10.1093/pnasnexus/pgaf307 · Cited by 3
A Genome-Wide Perspective on Metabolism
Rauch, A., & Mandrup, S. (2015) · Handbook of experimental pharmacology · doi:10.1007/164_2015_2 · Cited by 3
Shu, Q., Fan, J., Wang, B., & Shi, J. M. (2023) · Tetrahedron Letters · doi:10.1016/j.tetlet.2023.154888 · Cited by 3
Oliviero, G., Wynne, K. J., Andrews, D. C., Crean, J. K. G., Kölch, W., & Cagney, G. (2024) · Biomolecules · doi:10.3390/biom14070747 · Cited by 3
Zhao, B., Socha, J. J., Tóth, A., Fernandes, S., Warheit-Niemi, H. I., Ruff, B. P., Hershey, G. K. K., VanDussen, K. L., Swarr, D. T., & Zacharias, W. J. (2024) · American Journal of Respiratory Cell and Molecular Biology · doi:10.1165/rcmb.2024-0147oc · Cited by 3
YAMAZAKI, M., Fujie, H., & Miyoshi, H. (2020) · Journal of Biomechanical Science and Engineering · doi:10.1299/jbse.20-00083 · Cited by 3
Maderazo, D., Flegg, J. A., Algama, M., Ramialison, M., & Keith, J. M. (2022) · BMC Genomics · doi:10.1186/s12864-021-08190-0 · Cited by 3
Characterizing collaborative transcription regulation with a graph-based deep learning approach
Zhang, Z., Feng, F., Yao, Y., & Liu, J. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010162 · Cited by 3
Taking Stock of Regulatory Variation
Maurano, M. T., & Stamatoyannopoulos, J. A. (2015) · Cell Systems · doi:10.1016/j.cels.2015.07.011 · Cited by 3
Patrick, N. M., Griggs, C. A., Icenogle, A. L., Gilpatrick, M. M., Kadiyala, V., Jaime-Frias, R., & Smith, C. L. (2016) · The Journal of Steroid Biochemistry and Molecular Biology · doi:10.1016/j.jsbmb.2016.09.014 · Cited by 3
Liu, C., Zheng, Y., Li, X., Li, B., Wen, L., Wang, D., Feng, Q., & Jiang, C. (2021) · Evidence-based Complementary and Alternative Medicine · doi:10.1155/2021/6291428 · Cited by 3
Genome size variation and species diversity in salamandersPreprint
Herrick, J., & Sclavi, B. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/065425 · Cited by 3
Wang, J., Zhang, S., Lu, H., & Xu, H. (2021) · Research Square · doi:10.21203/rs.3.rs-711338/v1 · Cited by 3
GATA3 ZnF2-defective mutant condensation underlies type I IFN-activating in breast cancerPreprint
Chen, Y., Wan, Y., Pei, X., Wang, T., Ma, Z., & Chen, L. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.05.02.538687 · Cited by 3
Rise of the Chromodomain Helicase DNA‐Binding (CHD) Chromatin Remodelling Machines
Alendar, A. (2023) · Wiley eBooks · doi:10.1002/9780470015902.a0029448 · Cited by 3
Deng, H., Valenti, P., Payre, F., & Lim, B. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.03.17.643800 · Cited by 3
Neural crest induction requires SALL4-mediated BAF recruitment to lineage specific enhancers
Demurtas, M., Barnada, S. M., van Domselaar, E., Mitchell, Z. H., Deelen, L., & Trizzino, M. (2025) · Development · doi:10.1242/dev.205248 · Cited by 2
Heling, L. W. H. J., van der Veen, J., Rofe, A. P., West, E., Jiménez-Panizo, A., Alegre‐Martí, A., Sheikhhassani, V., Ng, J., Schmidt, T., Estébanez‐Perpiñá, E., et al. (2025) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2025.112634 · Cited by 2
Hu, Y., Wang, Y., Ye, M., He, Y., Ouyang, Z., Ren, C., Miao, T., Wang, S., Zhong, O., Liu, L., et al. (2026) · Nucleic Acids Research · doi:10.1093/nar/gkag173 · Cited by 2
Han, T., Oh, S., & Kang, K. (2015) · Genes & Genomics · doi:10.1007/s13258-015-0358-2 · Cited by 2
Models of Cancer Drug Discovery and Response to Therapy
Comandante-Lou, N., & Fallahi‐Sichani, M. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-801238-3.11356-x · Cited by 2
Huang, Z., Luo, S., Wang, Z., Zhang, Z., Jiang, B., Nie, Q. H., & Zhang, J. (2026) · eLife · doi:10.7554/elife.100623.4 · Cited by 2
Guo, S., Xu, Y., Zhou, Y., Liu, R., Wang, Y., Yao, L., Azam, S. M., Ma, H., Liu, X., Cao, S., et al. (2025) · Plants · doi:10.3390/plants14060880 · Cited by 2
It is time to take timing seriously in clinical genetics
Kosztolányi, G. (2014) · European Journal of Human Genetics · doi:10.1038/ejhg.2014.271 · Cited by 2
A Brief Introduction to Chromatin Regulation and Dynamics
Tzelepis, I., Martino, M., & Göndör, A. (2016) · Elsevier eBooks · doi:10.1016/b978-0-12-803395-1.00001-0 · Cited by 2
Leone, M., Galeota, E., Masseroli, M., & Pelizzola, M. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab815 · Cited by 2
Dissecting Steroid Receptor Function by Analytical Ultracentrifugation
Bain, D. L., Angelis, R. W. D., Connaghan, K. D., Yang, Q., DeGala, G. D., & Lambert, J. R. (2015) · Methods in enzymology on CD-ROM/Methods in enzymology · doi:10.1016/bs.mie.2015.04.005 · Cited by 2
Qin, Y., Liu, G., Li, Z., & Qu, Y. (2018) · Springer eBooks · doi:10.1007/978-981-13-0749-2_4 · Cited by 2
Induced Pluripotent Stem Cells
Mobley, A. S. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-811014-0.00004-4 · Cited by 4
Eickhardt, E. A., Als, T. D., Grove, J., Børglum, A. D., & Lescai, F. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/057604 · Cited by 2
Improved sensitivity and resolution of ATAC-seq differential DNA accessibility analysisPreprint
Sheikh, A. A., & Blais, A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.16.484118 · Cited by 2
Dynamic engagement of dual-role regulators by the Sin3 complexPreprint
Olivet, J., Shewakramani, N. R., Cesare, J., Laval, F., Nde, J., de Veire, J. V., Brammerloo, Y., Brebel, B., Debnath, O., Richardson, A. D., et al. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.26.708192 · Cited by 2
Lamins gate nuclear and chromatin structures for cardiomyocyte maturation genesPreprint
Bossone, K. A., Zheng, X., Kristiani, L., Marsela, R., Kim, Y., & Zheng, Y. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.20.726565 · Cited by 2
Krasova, N. S., Gladkih, A. I., Yaremenko, F. G., Лещенко, Ж., Колеснікова, А., Gromakovska, O. B., Lipson, V. V., & Poltorak, V. (2021) · PROBLEMS OF ENDOCRINE PATHOLOGY · doi:10.21856/j-pep.2021.2.10 · Cited by 1
Peak Scores Significantly Depend on the Relationships between Contextual Signals in ChIP-Seq Peaks
Vishnevsky, O. V., Bocharnikov, A. V., & Ignatieva, E. V. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25021011 · Cited by 1
Chen, Q., Cheng, H., Yu, H., Tian, H., & Chen, C. (2025) · Food Bioscience · doi:10.1016/j.fbio.2025.107128 · Cited by 1
Transcription factor degraders
Wang, M., Wei, Y., & Ma, X. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-21816-3.00006-3 · Cited by 1
Molecular Characterization of Three Novel Large Deletions Causing α0-Thalassemia
Ferrer, S., Andrés, M. P. R., Murúzabal, M. J., Nieto, J. M., González, F. A., Montero, B. O., Villegas, A., Benavente, C., & Ropero, P. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26188783 · Cited by 1
Gohil, R., Gao, Z., Lewis, R. A., Burkholder, N. T., Strahl, B. D., & Dowen, J. M. (2025) · Journal of Biological Chemistry · doi:10.1016/j.jbc.2025.110997 · Cited by 1
Muenstermann, C., Baracz, S. J., Heffernan, E. C., Lister, N. C., Waters, P. D., & Clemens, K. J. (2026) · Cellular and Molecular Neurobiology · doi:10.1007/s10571-026-01667-0 · Cited by 1
Molla, M. H. R., Abualreesh, M. H., Haridi, A., Khayat, M. F., Abir, K. M. S. S., & Jahan, B. (2026) · Toxicology and Environmental Health Sciences · doi:10.1007/s13530-026-00317-8 · Cited by 1
Metadata
- Authors
- Voss, T. C., & Hager, G. L.
- Affiliations
- National Institutes of Health (US)
- Corresponding author
- Hager, Gordon L.
- Venue
- Nature Reviews Genetics
- Published
- 2013-12-17
- Volume
- 15
- Issue
- 2
- Pages
- 69-81
- ISSN
- 1471-0056 (ISSN-L)
- 1471-0064
- PMC
- PMC6322398
- OpenAlex
- W2163353298
- Cited by
- 504
- References
- 124
- Citations by year
- 2026: 31 · 2025: 23 · 2024: 26 · 2023: 24 · 2022: 41 · 2021: 50 · 2020: 34 · 2019: 44 · 2018: 41 · 2017: 57 · 2016: 53 · 2015: 60 · 2014: 18
- FWCI
- 4.11
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Reviews Genetics (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- National Cancer Institute (Z01BC005450)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- chromatin, transcription factors, transcriptional regulation, chromatin reorganization, gene expression, stochastic gene expression, regulatory elements, nucleoprotein structure, chromatin dynamics
- MeSH terms
- Animals, Chromatin, Gene Expression Regulation, Humans, Models, Genetic, Nucleosomes, Protein Binding, Transcription Factors, Transcription, Genetic, Chromatin Assembly and Disassembly
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review