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The 4D nucleome project
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Abstract
The 4D Nucleome Network aims to develop and apply approaches to map the structure and dynamics of the human and mouse genomes in space and time with the goal of gaining deeper mechanistic insights into how the nucleus is organized and functions. The project will develop and benchmark experimental and computational approaches for measuring genome conformation and nuclear organization, and investigate how these contribute to gene regulation and other genome functions. Validated experimental technologies will be combined with biophysical approaches to generate quantitative models of spatial genome organization in different biological states, both in cell populations and in single cells.
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““4D mapping” of chromatin interactions (i.e., brain regions across developmental time) is critical for understanding the functional relationships of regulatory regions to genes (Dekker et al., 2017)”
From Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders (2019) · cites this paper as Dekker et al., 2017
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Cites
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
Self-citationA 3D Map of the Human Genome at Kilobase Resolution Reveals Principles of Chromatin Looping
Rao, S. S. P., Huntley, M. H., Durand, N. C., Stamenova, E. K., Bochkov, I. D., Robinson, J. T., Sanborn, A. L., Machol, I., Omer, A. D., Lander, E. S., et al. (2014) · Cell · doi:10.1016/j.cell.2014.11.021 · Cited by 9,212
Imaging Intracellular Fluorescent Proteins at Nanometer Resolution
Betzig, E., Patterson, G. H., Sougrat, R., Lindwasser, O. W., Olenych, S. G., Bonifacino, J. S., Davidson, M. W., Lippincott‐Schwartz, J., & Hess, H. F. (2006) · Science · doi:10.1126/science.1127344 · Cited by 8,941
Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome
Lieberman-Aiden, E., van Berkum, N. L., Williams, L., Imakaev, M., Ragoczy, T., Telling, A., Amit, I., Lajoie, B. R., Sabo, P. J., Dorschner, M. O., et al. (2009) · Science · doi:10.1126/science.1181369 · Cited by 8,898
Self-citationSub-diffraction-limit imaging by stochastic optical reconstruction microscopy (STORM)
Rust, M., Bates, M., & Zhuang, X. (2006) · Nature Methods · doi:10.1038/nmeth929 · Cited by 7,823
Topological domains in mammalian genomes identified by analysis of chromatin interactions
Dixon, J. R., Selvaraj, S., Yue, F., Kim, A., Li, Y., Shen, Y., Hu, M., Liu, J. S., & Ren, B. (2012) · Nature · doi:10.1038/nature11082 · Cited by 6,829
Self-citationIntegrative analysis of 111 reference human epigenomes
Roadmap Epigenomics Consortium, Kundaje, A., Meuleman, W., Ernst, J., Bilenky, M., Yen, A., Heravi-Moussavi, A., Kheradpour, P., Zhang, Z., Wang, J., et al. (2015) · Nature · doi:10.1038/nature14248 · Cited by 6,368
Self-citationSystematic Localization of Common Disease-Associated Variation in Regulatory DNA
Maurano, M. T., Humbert, R., Rynes, E., Thurman, R. E., Haugen, E., Wang, H., Reynolds, A. P., Sandstrom, R., Qu, H., Brody, J., et al. (2012) · Science · doi:10.1126/science.1222794 · Cited by 3,716
Ultra-High Resolution Imaging by Fluorescence Photoactivation Localization Microscopy
Hess, S. T., Girirajan, T. P. K., & Mason, M. D. (2006) · Biophysical Journal · doi:10.1529/biophysj.106.091116 · Cited by 3,684
Capturing Chromosome Conformation
Dekker, J., Rippe, K., Dekker, M., & Kleckner, N. (2002) · Science · doi:10.1126/science.1067799 · Cited by 3,652
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Items 101–200 of 762
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Cao, R. Y., Tian, H., Tian, Y., & Fu, X. (2023) · Advanced Science · doi:10.1002/advs.202302327 · Cited by 67
Advances and applications in single-cell and spatial genomics
Wang, J., Ye, F., Chai, H., Jiang, Y., Wang, T., Ran, X., Xia, Q., Xu, Z., Fu, Y., Zhang, G., et al. (2024) · Science China Life Sciences · doi:10.1007/s11427-024-2770-x · Cited by 70
Comparison of the Hi-C, GAM and SPRITE methods using polymer models of chromatin
Fiorillo, L., Musella, F., Conte, M., Kempfer, R., Chiariello, A. M., Bianco, S., Kukalev, A., Irastorza-Azcárate, I., Esposito, A., Abraham, A., et al. (2021) · Nature Methods · doi:10.1038/s41592-021-01135-1 · Cited by 73
Role of the Nucleus as a Sensor of Cell Environment Topography
Anselme, K., Wakhloo, N. T., Rougerie, P., & Pieuchot, L. (2017) · Advanced Healthcare Materials · doi:10.1002/adhm.201701154 · Cited by 67
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Wen, X., Luo, Z., Zhao, W., Calandrelli, R., Nguyen, T. C., Wan, X., Richard, J. L. C., & Zhong, S. (2024) · Nature · doi:10.1038/s41586-024-07239-w · Cited by 68
Self-citationHUGIn: Hi-C Unifying Genomic Interrogator
Martin, J. S., Xu, Z. Q., Reiner, A. P., Mohlke, K. L., Sullivan, P. F., Ren, B., Hu, M., & Li, Y. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx359 · Cited by 61
Self-citationKumar, S., Kaur, S., Seem, K., Kumar, S., & Mohapatra, T. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.774719 · Cited by 70
Enablers and challenges of spatial omics, a melting pot of technologies
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Geusz, R. J., Wang, A., Lam, D. K., Vinckier, N. K., Alysandratos, K., Roberts, D. A., Wang, J., Kefalopoulou, S., Ramirez, A., Qiu, Y., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26950-0 · Cited by 61
Self-citationAn integrated view of the structure and function of the human 4D nucleome
Dekker, J., Oksuz, B. A., Zhang, Y., Wang, Y., Minsk, M. K., Kuang, S., Yang, L., Gibcus, J. H., Krietenstein, N., Rando, O. J., et al. (2025) · Nature · doi:10.1038/s41586-025-09890-3 · Cited by 64
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Djekidel, M. N., Chen, Y., & Zhang, M. Q. (2018) · Genome Research · doi:10.1101/gr.212241.116 · Cited by 56
Nelson, G., Boehm, U., Bagley, S., Bajcsy, P., Bischof, J., Brown, C. M., Dauphin, A., Dobbie, I. M., Eriksson, J. E., Faklaris, O., et al. (2021) · Journal of Microscopy · doi:10.1111/jmi.13041 · Cited by 60
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Tasan, I., Šustáčková, G., Zhang, L., Kim, J., Sivaguru, M., HamediRad, M., Wang, Y., Genova, J., Ma, J., Belmont, A. S., et al. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky501 · Cited by 59
Self-citationMapping RNA–chromatin interactions by sequencing with iMARGI
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Self-citationEngineering 3D genome organization
Wang, H., Han, M., & Qi, L. S. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-020-00325-5 · Cited by 62
Determination of local chromatin interactions using a combined CRISPR and peroxidase APEX2 system
Qiu, W., Xu, Z., Zhang, M., Zhang, D., Fan, H., Li, T., Wang, Q., Liu, P., Zhu, Z., Du, D., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz134 · Cited by 56
Plant 3D genomics: the exploration and application of chromatin organization
Pei, L., Li, G., Lindsey, K., Zhang, X., & Wang, M. (2021) · New Phytologist · doi:10.1111/nph.17262 · Cited by 61
Childers, A. K., Geib, S. M., Sim, S. B., Poelchau, M. F., Coates, B. S., Simmonds, T. J., Scully, E. D., Smith, T. P. L., Childers, C. P., Corpuz, R. L., et al. (2021) · Insects · doi:10.3390/insects12070626 · Cited by 57
Calandrelli, R., Wen, X., Richard, J. L. C., Luo, Z., Nguyen, T. C., Chen, C.-J., Qi, Z., Xue, S., Chen, W., Yan, Z., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-42274-7 · Cited by 55
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Uffelmann, E., & Posthuma, D. (2020) · Biological Psychiatry · doi:10.1016/j.biopsych.2020.05.022 · Cited by 57
The biology and polymer physics underlying large‐scale chromosome organization
Sazer, S., & Schießel, H. (2017) · Traffic · doi:10.1111/tra.12539 · Cited by 54
Quinodoz, S. A., Bhat, P., Chovanec, P., Jachowicz, J. W., Ollikainen, N., Detmar, E., Soehalim, E., & Guttman, M. (2022) · Nature Protocols · doi:10.1038/s41596-021-00633-y · Cited by 58
Self-citationQuantifying DNA replication speeds in single cells by scEdU-seq
van den Berg, J., van Batenburg, V., Geisenberger, C., Tjeerdsma, R. B., Jaime-Soguero, A. D., Acebrón, S. P., van Vugt, M. A. T. M., & van Oudenaarden, A. (2024) · Nature Methods · doi:10.1038/s41592-024-02308-4 · Cited by 56
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Lee, S., Bakker, C., Vitzthum, C. M., Alver, B., & Park, P. J. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab870 · Cited by 53
Self-citationHammer, M., Huisman, M., Rigano, A., Boehm, U., Chambers, J. J., Gaudreault, N., North, A. J., Pimentel, J. A., Sudar, D., Bajcsy, P., et al. (2021) · Nature Methods · doi:10.1038/s41592-021-01327-9 · Cited by 53
Epiphany: predicting Hi-C contact maps from 1D epigenomic signals
Yang, R., Das, A., Gao, V. R., Karbalayghareh, A., Noble, W. S., Bilmes, J. A., & Leslie, C. S. (2023) · Genome biology · doi:10.1186/s13059-023-02934-9 · Cited by 54
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Murphy, D., Salataj, E., Giammartino, D. C. D., Rodriguez-Hernaez, J., Kloetgen, A., Garg, V., Char, E., Uyehara, C. M., Ee, L.-S., Lee, U., et al. (2023) · Nature Structural & Molecular Biology · doi:10.1038/s41594-023-01130-4 · Cited by 49
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Mizuno, A., & Okada, Y. (2019) · European Journal of Human Genetics · doi:10.1038/s41431-019-0468-4 · Cited by 57
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D’Incal, C. P., Rossem, K. E. V., Man, K. D., Konings, A., Dijck, A. V., Rizzuti, L., Vitriolo, A., Testa, G., Gozes, I., Berghe, W. V., et al. (2023) · Clinical Epigenetics · doi:10.1186/s13148-023-01450-8 · Cited by 52
Ultra-long-range interactions between active regulatory elementsPreprint
Friman, E. T., Flyamer, I. M., Marenduzzo, D., Boyle, S., & Bickmore, W. A. (2023) · Genome Research · doi:10.1101/gr.277567.122 · Cited by 51
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Lee, B., Wang, J., Cai, L., Kim, M., Namburi, S., Tjong, H., Feng, Y., Wang, P., Tang, Z., Abbas, A., et al. (2020) · Science Advances · doi:10.1126/sciadv.aay2078 · Cited by 48
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Mohanta, T. K., Mishra, A. K., & Al‐Harrasi, A. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222111585 · Cited by 51
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Feng, F., Tang, F., Gao, Y., Zhu, D., Li, T., Yang, S., Yao, Y., Huang, Y., & Liu, J. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac957 · Cited by 50
Gelléri, M., Chen, S., Szczurek, A., Hübner, B., Sterr, M., Neumann, J., Kröger, O., Sadlo, F., Imhoff, J., Markaki, Y., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2023.112567 · Cited by 46
Tozzi, A. (2019) · Physics of Life Reviews · doi:10.1016/j.plrev.2018.12.004 · Cited by 44
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Chomiak, A. A., Tiedemann, R. L., Liu, Y., Kong, X., Cui, Y., Wiseman, A. K., Thurlow, K. E., Cornett, E. M., Topper, M. J., Baylin, S. B., et al. (2024) · Science Advances · doi:10.1126/sciadv.adk4423 · Cited by 44
Lekschas, F., Peterson, B. K., Haehn, D., Ma, E. J., Gehlenborg, N., & Pfister, H. (2020) · Computer Graphics Forum · doi:10.1111/cgf.13971 · Cited by 41
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Zhang, Z., Feng, F., Qiu, Y., & Liu, J. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad436 · Cited by 38
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Han, X., Chen, S., Flynn, E. D., Wu, S., Wintner, D., & Shen, Y. (2018) · Nature Communications · doi:10.1038/s41467-018-04552-7 · Cited by 39
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Nelson, G., Boehm, U., Fernandez-Rodriguez, J., Ferrand, A., Gelman, L., Gheisari, A., Hartmann, H., Kukat, C., Laude, A., Mitkovski, M., et al. (2021) · The Journal of the American Medical Association (JAMA) Network (American Medical Association) · Cited by 39
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Rose, R., Peschke, N., Nigi, E., Gelléri, M., Ritz, S., Cremer, C. G., Luhmann, H. J., & Sinning, A. (2022) · Communications Biology · doi:10.1038/s42003-022-03704-2 · Cited by 42
Pujadas-Liwag, E. M., Wei, X., Acosta, N., Carter, L. M., Yang, J., Almassalha, L. M., Jain, S., Daneshkhah, A., Rao, S. S. P., Seker-Polat, F., et al. (2024) · Genome biology · doi:10.1186/s13059-024-03212-y · Cited by 38
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Bianco, S., Chiariello, A. M., Conte, M., Esposito, A., Fiorillo, L., Musella, F., & Nicodemi, M. (2020) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2020.01.002 · Cited by 41
Chromatin domains in space and their functional implications
Pontvianne, F., & Liu, C. (2019) · Current Opinion in Plant Biology · doi:10.1016/j.pbi.2019.11.005 · Cited by 43
Marsupial chromosomics: bridging the gap between genomes and chromosomes
Deakin, J. E., & Potter, S. (2019) · Reproduction Fertility and Development · doi:10.1071/rd18201 · Cited by 36
HiGlass: Web-based Visual Exploration and Analysis of Genome Interaction MapsPreprint
Kerpedjiev, P., Abdennur, N. A., Lekschas, F., McCallum, C., Dinkla, K., Strobelt, H., Luber, J. M., Ouellette, S., Azhir, A., Kumar, N., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/121889 · Cited by 43
Self-citationSpecies-specific regulation of XIST by the JPX/FTX orthologs
Rosspopoff, O., Cazottes, E., Huret, C., Loda, A., Collier, A., Casanova, M., Rugg-Gunn, P., Heard, E., Ouimette, J.-F., & Rougeulle, C. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad029 · Cited by 31
Native nucleosomes intrinsically encode genome organization principles
Park, S., Merino‐Urteaga, R., Karwacki-Neisius, V., Carrizo, G., Athreya, A., Marín-González, A., Benning, N. A., Park, J., Mitchener, M. M., Bhanu, N. V., et al. (2025) · Nature · doi:10.1038/s41586-025-08971-7 · Cited by 37
Computational methods for analyzing and modeling genome structure and organization
Lin, D., Bonora, G., Yardımcı, G. G., & Noble, W. S. (2018) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.1435 · Cited by 37
Practical Analysis of Hi-C Data: Generating A/B Compartment Profiles.
Miura, H., Poonperm, R., Takahashi, S., & Hiratani, I. (2018) · Methods in molecular biology · doi:10.1007/978-1-4939-8766-5_16 · Cited by 31
Electron tomography of plant organelles and the outlook for correlative microscopic approaches
Wang, P., Liang, Z., & Kang, B. (2019) · New Phytologist · doi:10.1111/nph.15882 · Cited by 35
High-resolution dynamic imaging of chromatin DNA communication using Oligo-LiveFISH
Zhu, Y., Balaji, A., Han, M., Andronov, L. P., Roy, A. R., Wei, Z., Chen, C., Miles, L., Cai, S., Gu, Z., et al. (2025) · Cell · doi:10.1016/j.cell.2025.03.032 · Cited by 38
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Golloshi, R., Sanders, J. T., & McCord, R. P. (2018) · Methods · doi:10.1016/j.ymeth.2018.04.033 · Cited by 28
RNAs as Proximity-Labeling Media for Identifying Nuclear Speckle Positions Relative to the Genome
Chen, W., Yan, Z., Li, S., Huang, N., Huang, X., Zhang, J., & Zhong, S. (2018) · iScience · doi:10.1016/j.isci.2018.06.005 · Cited by 33
Self-citationBresnick, E. H., & Johnson, K. D. (2019) · Blood Advances · doi:10.1182/bloodadvances.2019000378 · Cited by 32
Double-strand break toxicity is chromatin context independent
Friskes, A., Koob, L., Krenning, L., Severson, T., Koeleman, E. S., Vergara, X., Schubert, M., van den Berg, J., Evers, B., Manjón, A. G., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac758 · Cited by 32
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Sidiropoulos, N., Mardin, B. R., Rodríguez-González, F. G., Bochkov, I. D., Garg, S., Stütz, A. M., Korbel, J. O., Aiden, E. L., & Weischenfeldt, J. (2022) · Genome Research · doi:10.1101/gr.275790.121 · Cited by 32
4DNvestigator: time series genomic data analysis toolbox
Lindsly, S., Chen, C., Liu, S., Ronquist, S., Dilworth, S., Perlman, M. D., & Rajapakse, I. (2021) · Nucleus · doi:10.1080/19491034.2021.1910437 · Cited by 31
Epigenetic Regulation of Kaposi’s Sarcoma-Associated Herpesvirus Latency
Campbell, M., Yang, W.-S., Yeh, W. W., Kao, C.-H., & Chang, P. (2020) · Frontiers in Microbiology · doi:10.3389/fmicb.2020.00850 · Cited by 31
Epigenetic biomarkers and preterm birth
Park, B., Khanam, R., Vinayachandran, V., Baqui, A. H., London, S. J., & Biswal, S. S. (2020) · Current Zoology · doi:10.1093/eep/dvaa005 · Cited by 31
Qiu, G., Zheng, X., Fu, M., Huang, C., & Yang, X. (2021) · Ageing Research Reviews · doi:10.1016/j.arr.2021.101306 · Cited by 31
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Metadata
- Authors
- the 4D Nucleome Network, Dekker, J., Belmont, A. S., Guttman, M., Leshyk, V. O., Lis, J. T., Lomvardas, S., Mirny, L. A., O’Shea, C. C., Park, P. J., Ren, B., Politz, J. C. R., Shendure, J., & Zhong, S.
- Affiliations
- Howard Hughes Medical Institute (US)
- California Institute of Technology (US)
- Cornell University (US)
- Mortimer B. Zuckerman Mind Brain Behavior Institute (US)
- Salk Institute for Biological Studies (US)
- Harvard University (US)
- University of California San Diego (US)
- Corresponding author
- Dekker, Job
- ORCID
- Venue
- Nature
- Published
- 2017-09-14
- Volume
- 549
- Issue
- 7671
- Pages
- 219-226
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC5617335
- OpenAlex
- W2584394140
- Cited by
- 732
- References
- 118
- Citations by year
- 2026: 63 · 2025: 74 · 2024: 81 · 2023: 74 · 2022: 96 · 2021: 110 · 2020: 82 · 2019: 73 · 2018: 65 · 2017: 13
- FWCI
- 26.04
- Type
- journal article
- Language
- en
- Update notices
- erratum (2017-11-22)
- Open access
- bronze
- doi.org
- Locations
- Nature (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship@UMassChan (submittedVersion, cc-by-nc-nd)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- ReIn UW (University of Warsaw) (submittedVersion, cc-by-nc-nd)
- Funders
- National Institutes of Health
- National Heart, Lung, and Blood Institute (U01HL129998, U01HL129958)
- National Institute on Drug Abuse (U01DA040582)
- NIH Office of the Director
- National Cancer Institute (U01CA200060)
- National Institute on Deafness and Other Communication Disorders (R01DC013560)
- National Institute of General Medical Sciences (P50GM085764)
- National Institute of Diabetes and Digestive and Kidney Diseases (U54DK107977, U54DK107965, U54DK107980, U54DK107979)
- National Institute of Biomedical Imaging and Bioengineering (U01EB021223)
- Common Fund (1U01DA040709)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Nuclear Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Keywords
- 3D genome organization, nuclear organization, gene expression regulation, single-cell genomics, human genome, mouse genome, chromatin dynamics
- MeSH terms
- Animals, Cell Line, Cell Nucleus, Chromatin, Chromosomes, Goals, Humans, Models, Biological, Models, Molecular, Reproducibility of Results, Genome, Genomics, Information Dissemination, Mice, Molecular Imaging, Single-Cell Analysis, Spatio-Temporal Analysis
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