Single-cell Hi-C reveals cell-to-cell variability in chromosome structure

Comprehensive Mapping of Long-Range Interactions Reveals Folding Principles of the Human Genome

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Topological domains in mammalian genomes identified by analysis of chromatin interactions

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Capturing Chromosome Conformation

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Spatial partitioning of the regulatory landscape of the X-inactivation centre

Nora, E. P., Lajoie, B. R., Schulz, E. G., Giorgetti, L., Okamoto, I., Servant, N., Piolot, T., van Berkum, N. L., Meisig, J., Sedat, J., et al. (2012) · Nature · doi:10.1038/nature11049 · Cited by 2,895

Chromosome territories, nuclear architecture and gene regulation in mammalian cells

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Three-dimensional folding and functional organization principles of the Drosophila genome

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Nuclear organization of active and inactive chromatin domains uncovered by chromosome conformation capture–on-chip (4C)

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Chromosome Conformation Capture Carbon Copy (5C): A massively parallel solution for mapping interactions between genomic elementsPreprint

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Beyond the Sequence: Cellular Organization of Genome Function

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Active genes dynamically colocalize to shared sites of ongoing transcription

Osborne, C. S., Chakalova, L., Brown, K. E., Carter, D., Horton, A., Debrand, E., Goyenechea, B., Mitchell, J. A., Lopes, S. M. C. D. S., Reik, W., et al. (2004) · Nature Genetics · doi:10.1038/ng1423 · Cited by 1,080

GILoop: Robust chromatin loop calling across multiple sequencing depths on Hi-C data

Wang, F., Gao, T., Lin, J., Zheng, Z., Huang, L., Toseef, M., Li, X., & Wong, K. (2022) · iScience · doi:10.1016/j.isci.2022.105535 · Cited by 14

Combining fluorescence imaging with Hi-C to study 3D genome architecture of the same single cell

Lando, D., Basu, S., Stevens, T. J., Riddell, A., Wohlfahrt, K., Cao, Y., Boucher, W., Leeb, M., Atkinson, L. P., Lee, S. F., et al. (2018) · Nature Protocols · doi:10.1038/nprot.2018.017 · Cited by 13

The 3D genome: From fundamental principles to disease and cancer

Umlauf, D., & Mourad, R. (2018) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2018.07.002 · Cited by 15

Characterizing chromatin landscape from aggregate and single-cell genomic assays using flexible duration modeling

Gabitto, M. I., Rasmussen, A. W., Wapinski, O. L., Allaway, K. C., Carriero, N. J., Fishell, G., & Bonneau, R. (2020) · Nature Communications · doi:10.1038/s41467-020-14497-5 · Cited by 13

Discovery of new epigenomics-based biomarkers and the early diagnosis of neurodegenerative diseases

Lee, D., Choi, Y. H., Seo, J., Kim, J. K., & Lee, S. B. (2020) · Ageing Research Reviews · doi:10.1016/j.arr.2020.101069 · Cited by 14

Cell type-specific interchromosomal interactions as a mechanism for transcriptional diversityPreprint

Horta, A., Monahan, K., Bashkirova, E., & Lomvardas, S. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/287532 · Cited by 14

Live-cell 3D single-molecule tracking reveals how NuRD modulates enhancer dynamicsPreprint

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The oncomicrobiome: New insights into microorganisms in cancer

Ma, Y., Chen, T., Sun, T., Dilinuer, D., & Xiao, Y. (2024) · Microbial Pathogenesis · doi:10.1016/j.micpath.2024.107091 · Cited by 14

Nanoscale 3D DNA tracing in non-denatured cells resolves the Cohesin-dependent loop architecture of the genome in situ

Beckwith, K. S., Ødegård-Fougner, Ø., Morero, N. R., Barton, C., Schueder, F., Tang, W., Alexander, S., Peters, J. M., Jungmann, R., Birney, E., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-61689-y · Cited by 13

Single‐Cell and Spatial Omics: Methods and Applications

Cen, X., Huang, X., Deng, E., Gong, X., Tan, N., Ye, J. T., Wang, Y., Eils, R., Luo, Q., Li, Y., et al. (2026) · MedComm · doi:10.1002/mco2.70713 · Cited by 14

Polymer models are a versatile tool to study chromatin 3D organization

Esposito, A., Bianco, S., Fiorillo, L., Conte, M., Abraham, A., Musella, F., Nicodemi, M., Prisco, A., & Chiariello, A. M. (2021) · Biochemical Society Transactions · doi:10.1042/bst20201004 · Cited by 14

Epigenetics and tissue immunity—Translating environmental cues into functional adaptations*

Tuong, Z. K., Stewart, B. J., Guo, S. A., & Clatworthy, M. R. (2021) · Immunological Reviews · doi:10.1111/imr.13036 · Cited by 13

Subgraph extraction and graph representation learning for single cell Hi-C imputation and clustering

Zheng, J., Yang, Y., & Dai, Z. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad379 · Cited by 14

Hi-C, a chromatin 3D structure technique advancing the functional genomics of immune cells

Liu, R., Xu, R., Yan, S., Li, P., Jia, C., Sun, H., Sheng, K., Wang, Y., Zhang, Q., Guo, J., et al. (2024) · Frontiers in Genetics · doi:10.3389/fgene.2024.1377238 · Cited by 13

Cutting-edge tools for unveiling the dynamics of plasmid–host interactions

Yang, Q., Gao, J. T., Zhou, S. G., & Walsh, T. R. (2025) · Trends in Microbiology · doi:10.1016/j.tim.2024.12.013 · Cited by 13

Application of Deep Learning for Single Cell Multi-Omics: A State-of-the-Art Review

Wani, S. A., Khan, S. A., & Quadri, S. (2025) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-025-10230-x · Cited by 13

Retrospective and multifactorial single-cell profiling reveals sequential chromatin reorganization during X inactivation

Kefalopoulou, S., Rullens, P. M. J., de Luca, K. L., de Vries, S. S., Korthout, T., van Oudenaarden, A., Zeller, P. J., & Kind, J. (2025) · Nature Cell Biology · doi:10.1038/s41556-025-01687-w · Cited by 12

Expressed alleles of imprinted IGF2, DLK1 and MEG3 colocalize in 3D-preserved nuclei of porcine fetal cells

Lahbib-Mansais, Y., Barasc, H., Marti-Marimon, M., Mompart, F., Iannuccelli, E., Robelin, D., Riquet, J., & Martine Yerle, B. (2016) · BMC Cell Biology · doi:10.1186/s12860-016-0113-9 · Cited by 14

A (3D-Nuclear) Space Odyssey: Making Sense of Hi-C Maps

Mota-Gómez, I., & Lupiáñez, D. G. (2019) · Genes · doi:10.3390/genes10060415 · Cited by 16

Technologies to study spatial genome organization: beyond 3C

Übelmesser, N., & Papantonis, A. (2019) · Briefings in Functional Genomics · doi:10.1093/bfgp/elz019 · Cited by 13

Broadening our understanding of the genetics of Juvenile Idiopathic Arthritis (JIA): Interrogation of three dimensional chromatin structures and genetic regulatory elements within JIA-associated risk loci

Jiang, K., Kessler, H. A., Park, Y., Sudman, M., Thompson, S. D., & Jarvis, J. N. (2020) · PLoS ONE · doi:10.1371/journal.pone.0235857 · Cited by 13

Deciphering the Complexity of 3D Chromatin Organization Driving Lymphopoiesis and Lymphoid Malignancies

Scourzic, L., Salataj, E., & Apostolou, E. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.669881 · Cited by 16

The two waves in single-cell 3D genomics

Ulianov, S. V., & Razin, S. V. (2021) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2021.05.021 · Cited by 15

Major Reorganization of Chromosome Conformation During Muscle Development in Pig

Marti-Marimon, M., Vialaneix, N., Lahbib-Mansais, Y., Zytnicki, M., Camut, S., Robelin, D., Martine Yerle, B., & Foissac, S. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.748239 · Cited by 13

FISH Going Meso-Scale: A Microscopic Search for Chromatin Domains

Maslova, A., & Krasikova, A. (2021) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2021.753097 · Cited by 16

Mapping chromatin loops in single cells

Yu, M., Li, Y., & Hu, M. (2022) · Trends in Genetics · doi:10.1016/j.tig.2022.03.007 · Cited by 10

Comparison and critical assessment of single-cell Hi-C protocols

Gridina, M. M., Taskina, A., Lagunov, T. A., Nurislamov, A. R., Kulikova, T., Krasikova, A., & Fishman, V. (2022) · Heliyon · doi:10.1016/j.heliyon.2022.e11023 · Cited by 12

The Interplay of Transcription and Genome Topology Programs T Cell Development and Differentiation

Zhao, X., Zhu, S., Peng, W., & Xue, H. (2022) · The Journal of Immunology · doi:10.4049/jimmunol.2200625 · Cited by 14

Approaches for Modes of Action Study of Long Non-Coding RNAs: From Single Verification to Genome-Wide Determination

Tao, X., Li, S., Chen, G., Wang, J., & Xu, S. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms24065562 · Cited by 13

Exploring the mechanisms of genome-wide long-range interactions: interpreting chromosome organization

Wang, J., Meng, X., Chen, H., Yuan, C., Li, X., Zhou, Y., & Chen, M. (2016) · Briefings in Functional Genomics · doi:10.1093/bfgp/elv062 · Cited by 12

Real‐Time Chiral Metabolic Monitoring of Single Cell Using Microchip Electrophoresis Coupled with Electrospray Ionization Mass Spectrometry

Li, X., Zhao, S., & Liu, Y. (2016) · ChemistrySelect · doi:10.1002/slct.201600748 · Cited by 13

The Role of Chromatin Density in Cell Population Heterogeneity during Stem Cell Differentiation

Golkaram, M., Jang, J., Hellander, S., Kosik, K. S., & Petzold, L. R. (2017) · Scientific Reports · doi:10.1038/s41598-017-13731-3 · Cited by 14

Nuclear Architecture in the Nervous System: Development, Function, and Neurodevelopmental Diseases

Ito, K., & Takizawa, T. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00308 · Cited by 13

Epigenomic technologies for precision oncology

Weichenhan, D., Lipka, D. B., Lutsik, P., Goyal, A., & Plass, C. (2020) · Seminars in Cancer Biology · doi:10.1016/j.semcancer.2020.08.004 · Cited by 15

Understanding Regulatory Mechanisms of Brain Function and Disease through 3D Genome Organization

Liu, W., Zhong, W., Chen, J. C., Huang, B., Hu, M., & Li, Y. (2022) · Genes · doi:10.3390/genes13040586 · Cited by 11

Perturbing Chromatin Structure to Understand Mechanisms of Gene ExpressionPreprint

Bartman, C., & Blobel, G. A. (2015) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.2015.80.027359 · Cited by 13

Rearrangement of macronucleus chromosomes correspond to TAD-like structures of micronucleus chromosomes in Tetrahymena thermophilaPreprint

Luo, Z., Hu, T., Jiang, H., Wang, R., Xu, Q., Zhang, S. V., Cao, J., & Song, X. (2020) · Genome Research · doi:10.1101/gr.241687.118 · Cited by 17

Transcriptomics

Anthony, D. S.-B., Chen, C. J., Nixon, B., & Hondermarck, H. (2022) · Elsevier eBooks · doi:10.1016/b978-0-12-821618-7.00157-7 · Cited by 16

Gene regulatory landscape dissected by single-cell four-omics sequencing

Chen, Y., Liu, Z., Xu, H., Liu, J., Wang, M., Chi, Y., LIANG, B., Liu, M., Peng, Y., Ge, H., et al. (2026) · Nature · doi:10.1038/s41586-026-10322-z · Cited by 15

scGAD: single-cell gene associating domain scores for exploratory analysis of scHi-C data

Shen, S., Zheng, Y., & Keleş, S. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac372 · Cited by 12

HiCImpute: A Bayesian hierarchical model for identifying structural zeros and enhancing single cell Hi-C data

Xie, Q. S., Han, C., Jin, V. X., & Lin, S. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010129 · Cited by 12

Long range inter-chromosomal interaction of Oct4 distal enhancer loci regulates ESCs pluripotency

Moon, B.-S., Huang, D., Gao, F., Cai, M., Lyu, G., Zhang, L., Chen, J., & Lu, W. (2023) · Cell Death Discovery · doi:10.1038/s41420-023-01363-8 · Cited by 11

Single-cell Hi-C data enhancement with deep residual and generative adversarial networks

Wang, Y., Guo, Z., & Cheng, J. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad458 · Cited by 13

DNA-GPS: A theoretical framework for optics-free spatial genomics and synthesis of current methods

Greenstreet, L., Afanassiev, A., Kijima, Y., Heitz, M., Ishiguro, S., King, S. B., Yachie, N., & Schiebinger, G. R. (2023) · Cell Systems · doi:10.1016/j.cels.2023.08.005 · Cited by 15

Single-cell epigenomics and proteomics methods integrated in multiomics

Bi, H., & Weng, X. (2024) · Fundamental Research · doi:10.1016/j.fmre.2023.11.014 · Cited by 12

Deep generative models in single-cell omics

Rivero-García, I., Torres, M., & Sánchez‐Cabo, F. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108561 · Cited by 13

Are We There Yet? Assessing the Readiness of Single-Cell Proteomics to Answer Biological Hypotheses

Nitz, A. A., Chavez, J. H. G., Eliason, Z. G., & Payne, S. (2024) · Journal of Proteome Research · doi:10.1021/acs.jproteome.4c00091 · Cited by 16

Chromatin in situ Proximity (ChrISP): Single-Cell Analysis Of Chromatin Proximities at a High Resolution

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3D modeling of chromatin structure: is there a way to integrate and reconcile single cell and population experimental data?

Dily, F. L., Serra, F., & Martı́-Renom, M. A. (2017) · Wiley Interdisciplinary Reviews Computational Molecular Science · doi:10.1002/wcms.1308 · Cited by 14

RNA Biogenesis Instructs Functional Inter-Chromosomal Genome Architecture

Bertero, A. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.645863 · Cited by 12

Advances in higher-order chromatin architecture: the move towards 4D genome

Jung, N., & Kim, T.-K. (2021) · BMB Reports · doi:10.5483/bmbrep.2021.54.5.035 · Cited by 14

Predictive Polymer Models for 3D Chromosome Organization

Chiang, M., Forte, G., Gilbert, N., Marenduzzo, D., & Brackley, C. A. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-1390-0_14 · Cited by 16

Decoding the Equine Genome: Lessons from ENCODE

Peng, S., Petersen, J. L., Bellone, R. R., Kalbfleisch, T., Kingsley, N. B., Barber, A. M., Cappelletti, E., Giulotto, E., & Finno, C. J. (2021) · Genes · doi:10.3390/genes12111707 · Cited by 10

Approaches of Single-Cell Analysis in Crop Improvement

Srivastava, U., & Singh, S. (2022) · Springer protocols handbooks/Springer protocols · doi:10.1007/978-1-0716-2533-0_14 · Cited by 12

Distance-based assessment of the localization of functional annotations in 3D genome reconstructions

Capurso, D., & Segal, M. R. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-992 · Cited by 12

Changes in the organization of the genome during the mammalian cell cycle

Giorgetti, L., Servant, N., & Heard, É. (2013) · Genome biology · doi:10.1186/gb4147 · Cited by 11

Large-scale 3D chromatin reconstruction from chromosomal contacts

Zhang, Y., Liu, W., Lin, Y., Ng, Y. K., & Li, S. C. (2019) · BMC Genomics · doi:10.1186/s12864-019-5470-2 · Cited by 13

Visualising three-dimensional genome organisation in two dimensions

Ing‐Simmons, E., & Vaquerizas, J. M. (2019) · Development · doi:10.1242/dev.177162 · Cited by 13

Advances in profiling chromatin architecture shed light on the regulatory dynamics underlying brain disorders

Pratt, B. M., & Won, H. (2021) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2021.08.013 · Cited by 13

Dynamic and equilibrium properties of finite-size polymer models of chromosome folding

Conte, M., Fiorillo, L., Annunziatella, C., Esposito, A., Musella, F., Abraham, A., Bianco, S., & Chiariello, A. M. (2021) · Physical review. E · doi:10.1103/physreve.104.054402 · Cited by 14

When 3D genome technology meets viral infection, including SARS‐CoV‐2

Liang, W., Wang, S., Wang, H., Li, X., Meng, Q., Zhao, Y., & Zheng, C. (2022) · Journal of Medical Virology · doi:10.1002/jmv.28040 · Cited by 10

Influence of nuclear structure on the formation of radiation-induced lethal lesions

Friedman, D., Tait, L. M., & Vaughan, A. T. (2016) · International Journal of Radiation Biology · doi:10.3109/09553002.2016.1144941 · Cited by 13

Three‐dimensional genome architecture in health and disease

Ouimette, J., Rougeulle, C., & Veitia, R. A. (2018) · Clinical Genetics · doi:10.1111/cge.13219 · Cited by 15

Modeling three-dimensional genomic organization in evolution and pathogenesis

Diament, A., & Tuller, T. (2018) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2018.07.008 · Cited by 11

Concurrent profiling of multiscale 3D genome organization and gene expression in single mammalian cellsPreprint

Zhou, T., Zhang, R., Jia, D., Doty, R. T., Munday, A. D., Gao, D., Xin, L., Abkowitz, J. L., Duan, Z., & Ma, J. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.07.20.549578 · Cited by 12

Chromatin insulators in gene regulation and 3D genome organization

Sultana, H., Kunar, R., & Matera, A. G. (2025) · Biochemical Society Transactions · doi:10.1042/bst20253036 · Cited by 11

Inferring Single-Cell 3D Chromosomal Structures Based on the Lennard-Jones Potential

zha, M., Wang, N., Zhang, C., & Wang, Z. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22115914 · Cited by 12

Intra- and interchromosomal contact mapping reveals the Igh locus has extensive conformational heterogeneity and interacts with B-lineage genes

Mielczarek, O., Rogers, C. H., Zhan, Y., Matheson, L. S., Stubbington, M. J. T., Schoenfelder, S., Bolland, D. J., Javierre, B. M., Wingett, S., Várnai, C., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.113074 · Cited by 12

Interplay between epigenome and 3D chromatin structure

Han, M.-H., Issagulova, D., & Park, M. (2023) · BMB Reports · doi:10.5483/bmbrep.2023-0197 · Cited by 13

Genome folding by cohesin

Qi, S., Shi, Z., & Yu, H. (2025) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2025.102310 · Cited by 13

Single‐Cell Hi‐C Technologies and Computational Data Analysis

Dautle, M., & Chen, Y. (2025) · Advanced Science · doi:10.1002/advs.202412232 · Cited by 12

Single-Cell Sequencing Technology in Oncology: Applications for Clinical Therapies and Research

Ye, B., Qingping, G., Zeng, Z. R., Stary, C. M., Jian, Z., Xiong, X., & Gu, L. (2016) · Analytical Cellular Pathology · doi:10.1155/2016/9369240 · Cited by 11

A novel method for discovering local spatial clusters of genomic regions with functional relationships from DNA contact maps

Hu, X. S., Shi, C. H., & Yip, K. Y.-L. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw256 · Cited by 11

A Compendium of Methods to Analyze the Spatial Organization of Plant Chromatin

Probst, A. V. (2017) · Methods in molecular biology · doi:10.1007/978-1-4939-7318-7_23 · Cited by 11

Use of 3D imaging for providing insights into high-order structure of mitotic chromosomes

Yusuf, M., Kaneyoshi, K., Fukui, K., & Robinson, I. K. (2018) · Chromosoma · doi:10.1007/s00412-018-0678-5 · Cited by 11

BPscore: An Effective Metric for Meaningful Comparisons of Structural Chromosome Segmentations

Zaborowski, R., & Wilczyński, B. (2019) · Journal of Computational Biology · doi:10.1089/cmb.2018.0162 · Cited by 11

New insights into promoter–enhancer communication mechanisms revealed by dynamic single-molecule imaging

Li, J., & Pertsinidis, A. (2021) · Biochemical Society Transactions · doi:10.1042/bst20200963 · Cited by 10

Hi-CO: 3D genome structure analysis with nucleosome resolution

Ohno, M., Ando, T., Priest, D. G., & Taniguchi, Y. (2021) · Nature Protocols · doi:10.1038/s41596-021-00543-z · Cited by 12

Epigenome rewiring in human pluripotent stem cells

Yan, J., & Huangfu, D. (2021) · Trends in Cell Biology · doi:10.1016/j.tcb.2021.12.001 · Cited by 11

Machine Learning Approaches to Single-Cell Data Integration and Translation

Uhler, C., & Shivashankar, G. V. (2022) · Proceedings of the IEEE · doi:10.1109/jproc.2022.3166132 · Cited by 11

Community-driven ELIXIR activities in single-cell omics

Czarnewski, P., Mahfouz, A. E., Calogero, R., Palagi, P. M., Portell-Silva, L., Gonzalez‐Uriarte, A., Soneson, C., Burdett, T., Szomolay, B., Videm, P., et al. (2022) · F1000Research · doi:10.12688/f1000research.122312.1 · Cited by 11

Topological implications of DNA tumor viral episomes

Kim, E. T., & Kim, K.-D. (2022) · BMB Reports · doi:10.5483/bmbrep.2022.55.12.154 · Cited by 11

Integration of 3D genome topology and local chromatin features uncovers enhancers underlying craniofacial-specific cartilage defects

Chen, Q., Dai, J., & Bian, Q. (2022) · Science Advances · doi:10.1126/sciadv.abo3648 · Cited by 11

Capturing the hierarchically assorted modules of protein–protein interactions in the organized nucleome

Dai, S., Liu, S., Zhou, C., Yu, F., Zhu, G., Zhang, W., Deng, H., Burlingame, A. L., Yu, W., Wang, T., et al. (2023) · Molecular Plant · doi:10.1016/j.molp.2023.03.013 · Cited by 11

Supervised learning method for predicting chromatin boundary associated insulator elements

Bednarz, P., & Wilczyński, B. (2014) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720014420062 · Cited by 11

Roles of chromatin insulators in the formation of long-range contacts

Gall, A. L., Valeri, A., & Nöllmann, M. (2015) · Nucleus · doi:10.1080/19491034.2015.1010962 · Cited by 11

How computer science can help in understanding the 3D genome architecture

Shavit, Y., Merelli, I., Milanesi, L., & Lió, P. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbv085 · Cited by 12

Developing bioimaging and quantitative methods to study 3D genome

Gao, J. T., Yang, X., Djekidel, M. N., Wang, Y., Xi, P., & Zhang, M. Q. (2016) · Quantitative Biology · doi:10.1007/s40484-016-0065-2 · Cited by 11

A minimal Gō-model for rebuilding whole genome structures from haploid single-cell Hi-C data

Wettermann, S., Brems, M. A., Siebert, J. T., Vu, G. T., Stevens, T. J., & Virnau, P. (2019) · Computational Materials Science · doi:10.1016/j.commatsci.2019.109178 · Cited by 11

Transcription Factors Indirectly Regulate Genes through Nuclear Colocalization

Dai, Z. (2019) · Cells · doi:10.3390/cells8070754 · Cited by 11

Single-cell transcriptomics uncover distinct innate and adaptive cell subsets during tissue homeostasis and regeneration

Yang, Y., Ku, M., & Lui, K. O. (2020) · Journal of Leukocyte Biology · doi:10.1002/jlb.6mr0720-131r · Cited by 12

Systems-level chromosomal parameters represent a suprachromosomal basis for the non-random chromosomal arrangement in human interphase nuclei

Fatakia, S. N., Mehta, I. S., & Rao, B. J. (2016) · Scientific Reports · doi:10.1038/srep36819 · Cited by 10

Super‐resolution microscopy of genome organization

Shim, S. (2021) · Genes & Genomics · doi:10.1007/s13258-021-01044-9 · Cited by 11

Improving 3D Genome Reconstructions Using Orthologous and Functional Constraints

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