The 4D nucleome project

An integrated encyclopedia of DNA elements in the human genome

The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072

A 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

Sub-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

Integrative 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

Systematic 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

Cytogenetics and Cytogenomics in Clinical Diagnostics: Genome Architecture, Structural Variants, and Translational Applications

Federico, C., Brancato, D., Bruno, F., Coniglio, E., Sturiale, V., & Saccone, S. (2025) · Genes · doi:10.3390/genes16070780 · Cited by 16

Interchromosomal interactions with meaning for disease

Weise, A., & Liehr, T. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823579-9.00014-x · Cited by 13

Regulation of Gene Expression by Telomere Position Effect

Lee, K., Kim, D., & Kim, W. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222312807 · Cited by 16

DeepLUCIA: predicting tissue-specific chromatin loops using Deep Learning-based Universal Chromatin Interaction Annotator

Yang, D., Chung, T., & Kim, D. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac373 · Cited by 13

Transcription factor expression is the main determinant of variability in gene co‐activity

van Duin, L., Krautz, R., Rennie, S., & Andersson, R. (2023) · Molecular Systems Biology · doi:10.15252/msb.202211392 · Cited by 11

3D genome organization and epigenetic regulation in autoimmune diseases

Qiu, Y., Feng, D., Jiang, W., Zhang, T., Lu, Q., & Zhao, M. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1196123 · Cited by 12

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

Machine Learning Reveals the Diversity of Human 3D Chromatin Contact Patterns

Gilbertson, E. N., Brand, C. M., McArthur, E., Rinker, D. C., Kuang, S., Pollard, K. S., & Capra, J. A. (2024) · Molecular Biology and Evolution · doi:10.1093/molbev/msae209 · Cited by 13

Interplay between cohesin and RNA polymerase II in regulating chromatin interactions and gene transcription

Kim, M., Wang, P., Clow, P. A., Chien, E., Wang, X., Peng, J., Chai, H., Liu, X., Lee, B., Ngan, C. Y., et al. (2026) · Nature Structural & Molecular Biology · doi:10.1038/s41594-025-01708-0 · Cited by 13

COMBO-FISH: A Versatile Tool Beyond Standard FISH to Study Chromatin Organization by Fluorescence Light Microscopy

Lee, J., Tchetgna, F. L. D., Krufczik, M., Schmitt, E., Cremer, C. G., estvater, F. B., & Hausmann, M. (2019) · OBM Genetics · doi:10.21926/obm.genet.1901064 · Cited by 13

Reflections on the organization and the physical state of chromatin in eukaryotic cells

Strickfaden, H. (2020) · Genome · doi:10.1139/gen-2020-0132 · Cited by 14

Leveraging cell-type-specific regulatory networks to interpret genetic variants in abdominal aortic aneurysm

Ma, S., Chen, X., Zhu, X., Tsao, P. S., & Wong, W. H. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2115601119 · Cited by 13

Asymmetric sandwiched nanofibrillated cellulose composites prepared by one-pot vacuum filtration for ultrahigh electromagnetic interference shielding

Qi, W., Zeng, L., Xue, B., Wu, C., Mai, X., Xie, L., & Zheng, Q. (2024) · Materials & Design · doi:10.1016/j.matdes.2024.112828 · Cited by 13

Tibanna: software for scalable execution of portable pipelines on the cloud

Lee, S., Johnson, J., Vitzthum, C. M., Kırlı, K., Alver, B., & Park, P. J. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz379 · Cited by 13

Architectural proteins for the formation and maintenance of the 3D genome

Li, M., Gan, J., Sun, Y., Xu, Z., Yang, J., Sun, Y., & Li, C. (2020) · Science China Life Sciences · doi:10.1007/s11427-019-1613-3 · Cited by 15

Inferring chromosome radial organization from Hi-C data

Das, P., Shen, T., & McCord, R. P. (2020) · BMC Bioinformatics · doi:10.1186/s12859-020-03841-7 · Cited by 13

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

Single cell analysis reveals dynamics of transposable element transcription following epigenetic de-repressionPreprint

Brocks, D., Chomsky, E., Mukamel, Z., Lifshitz, A., & Tanay, A. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/462853 · Cited by 10

Mustache: Multi-scale Detection of Chromatin Loops from Hi-C and Micro-C Maps using Scale-Space RepresentationPreprint

Ardakany, A. R., Gezer, H. T., Lonardi, S., & Ay, F. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.02.24.963579 · Cited by 13

EPInformer: A Scalable Deep Learning Framework for Gene Expression Prediction by Integrating Promoter-enhancer Sequences with Multimodal Epigenomic DataPreprint

Lin, J., Luo, R., & Pinello, L. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.08.01.606099 · Cited by 13

Exonuclease combinations reduce noises in 3D genomics technologies

Kong, S., Li, Q., Zhang, G., Li, Q., Huang, Q., Huang, L., Zhang, H., Huang, Y., Peng, Y., Qin, B., et al. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa106 · Cited by 12

Technological advancements in deciphering RNA-RNA interactions

Ye, R., Zhao, H., Wang, X., & Xue, Y. (2024) · Molecular Cell · doi:10.1016/j.molcel.2024.06.036 · Cited by 12

DNALONGBENCH: a benchmark suite for long-range DNA prediction tasks

Cheng, W., Song, Z., Zhang, Y., Wang, S., Wang, D., Yang, M., Li, L., & Ma, J. (2025) · Nature Communications · doi:10.1038/s41467-025-65077-4 · Cited by 20

Computational methods for analyzing genome-wide chromosome conformation capture data

Nicoletti, C., Forcato, M., & Bicciato, S. (2018) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2018.01.023 · Cited by 14

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

Large-scale data-driven and physics-based models offer insights into the relationships among the structures, dynamics, and functions of chromosomes

Feng, C., Wang, J., & Chu, X. (2023) · Journal of Molecular Cell Biology · doi:10.1093/jmcb/mjad042 · Cited by 12

Epigenetic Regulation of Chromatin in Prostate Cancer

Natesan, R., Aras, S., Effron, S. S., & Asangani, I. A. (2019) · Advances in experimental medicine and biology · doi:10.1007/978-3-030-32656-2_17 · Cited by 12

Genome organization in proximity to the BAP1 locus appears to play a pivotal role in a variety of cancers

Sharma, A., Liu, H., Tobar-Tosse, F., Noll, A., Dakal, T. C., Li, H., Holz, F. G., Loeffler, K. U., & Herwig‐Carl, M. C. (2020) · Cancer Science · doi:10.1111/cas.14319 · Cited by 12

Driven progressive evolution of genome sequence complexity in Cyanobacteria

Moyá, A., Oliver, J. L. T., Verdú, M., Delaye, L., Arnau, V., Bernaola‐Galván, P., de la Fuente, R., Dı́az-Villanueva, W., Gómez‐Martín, C., González, F. M., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-76014-4 · Cited by 15

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

Storage, visualization, and navigation of 3D genomics data

Waldispühl, J., Zhang, E., Butyaev, A., Nazarova, E., & Cyr, Y. (2018) · Methods · doi:10.1016/j.ymeth.2018.05.008 · Cited by 13

Towards community-driven metadata standards for light microscopy: tiered specifications extending the OME modelPreprint

Hammer, 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) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.25.441198 · Cited by 12

Comparing genomic and epigenomic features across species using the WashU Comparative Epigenome BrowserPreprint

Zhuo, X., Hsu, S., Purushotham, D., Kuntala, P. K., Harrison, J. K., Du, A. Y., Chen, S., Li, D., & Wang, T. (2023) · Genome Research · doi:10.1101/gr.277550.122 · Cited by 12

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

Super RNA Pol II domains enhance minor ZGA through 3D interaction to ensure the integrity of major transcriptional waves in late-ZGA mammals

Zhang, J., Li, H., Li, L., Wu, J., Song, L., Liu, X., Pan, Z., Zhou, C., Li, W., Liu, Z., et al. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.100856 · Cited by 13

Nucleosome dynamics of human iPSC during neural differentiation

Harwood, J. C., Kent, N. A., Allen, N. D., & Harwood, A. J. (2019) · EMBO Reports · doi:10.15252/embr.201846960 · Cited by 11

Functional genomics links genetic origins to pathophysiology in neurodegenerative and neuropsychiatric disease

Wamsley, B., & Geschwind, D. H. (2020) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2020.05.032 · 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

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

Imaging Method Using CRISPR/dCas9 and Engineered gRNA Scaffolds Can Perturb Replication Timing at the HSPA1 Locus

Xiong, X., Tasan, I., Yang, C., Zhang, M., Gonzalez, G. A. H., Liu, S., Chaturvedi, P., Belmont, A. S., & Zhao, H. (2023) · ACS Synthetic Biology · doi:10.1021/acssynbio.2c00433 · Cited by 11

Streamlined histone-based fluorescence lifetime imaging microscopy (FLIM) for studying chromatin organisation

Sherrard, A., Bishop, P., Panagi, M., Villagomez, M. B., Alibhai, D., & Kaidi, A. (2018) · Biology Open · doi:10.1242/bio.031476 · Cited by 11

Remodeling the chromatin landscape in T lymphocytes by a division of labor among transcription factors

Vahedi, G. (2021) · Immunological Reviews · doi:10.1111/imr.12942 · Cited by 11

Integrative approaches in genome structure analysis

Boninsegna, L., Yıldırım, A., Zhan, Y., & Alber, F. (2021) · Structure · doi:10.1016/j.str.2021.12.003 · Cited by 11

Genome dimensions control biological and toxicological functions; myth or reality?

Wang, D. C., & Wang, X. (2018) · Cell Biology and Toxicology · doi:10.1007/s10565-018-9440-2 · Cited by 11

Dynamic chromatin organization and regulatory interactions in human endothelial cell differentiation

Alavattam, K. G., Mitzelfelt, K. A., Bonora, G., Fields, P., Yang, X., Chiu, H. S., Pabon, L., Bertero, A., Palpant, N. J., Noble, W. S., et al. (2022) · Stem Cell Reports · doi:10.1016/j.stemcr.2022.11.003 · Cited by 10

Sulfobetaine-Phosphonate Block Copolymer Coated Iron Oxide Nanoparticles for Genomic Locus Targeting and Magnetic Micromanipulation in the Nucleus of Living Cells

Delille, F., Balloul, É., Hajj, B., Hanafi, M., Morand, C., Xu, X. Z., Dumas, S., Coulon, A., Lequeux, N., & Pons, T. (2023) · Nano Letters · doi:10.1021/acs.nanolett.3c00688 · Cited by 10

Chromosomal positioning and epigenetic architecture influence DNA methylation patterns triggered by galactic cosmic radiation

Perdyan, A., Jąkalski, M., Horbacz, M., Beheshti, A., & Mieczkowski, J. (2024) · Scientific Reports · doi:10.1038/s41598-024-51756-7 · Cited by 11

Image-based 3D genomics through chromatin tracing

Yang, T., & Wang, S. (2024) · Nature Reviews Methods Primers · doi:10.1038/s43586-024-00354-y · Cited by 10

Landscape of the Epstein-Barr virus-host chromatin interactome and gene regulation

Tian, S., Yang, Y., Ning, D., Yu, T., Gao, T., Deng, Y., Fang, K., Xu, Y., Jing, K., Huang, G., et al. (2025) · EMBO Journal · doi:10.1038/s44318-025-00466-5 · Cited by 8

Loop Catalog: a comprehensive HiChIP database of human and mouse samples

Reyna, J., Fetter, K., Ignacio, R., Marandi, C. C. A., Ma, A., Rao, N., Jiang, Z., Figueroa, D. S., Bhattacharyya, S., & Ay, F. (2025) · Genome biology · doi:10.1186/s13059-025-03615-5 · Cited by 9

The extracellular vesicle transcriptome provides tissue-specific functional genomic annotation relevant to disease susceptibility in obesity

Chatterjee, E., Betti, M. J., Sheng, Q., Lin, P., Emont, M. P., Li, G., Amancherla, K. V., García-Contreras, M., Gokulnath, P., Limpitikul, W. B., et al. (2025) · Cell Genomics · doi:10.1016/j.xgen.2025.100925 · Cited by 10

DeepChIA-PET: Accurately predicting ChIA-PET from Hi-C and ChIP-seq with deep dilated networks

Liu, T., & Wang, Z. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011307 · Cited by 10

Druggable Transcriptional Networks in the Human Neurogenic Epigenome

Higgins, G. A., Williams, A. M., Ade, A. S., Alam, H. B., & Athey, B. D. (2019) · Pharmacological Reviews · doi:10.1124/pr.119.017681 · Cited by 10

Histone H3 Lysine 56 Acetylation Is Required for Formation of Normal Levels of Meiotic DNA Breaks in S. cerevisiae

Karányi, Z., Hornyák, L., & Székvölgyi, L. (2020) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2019.00364 · Cited by 10

Expanded ENCODE delivers invaluable genomic encyclopedia

Hon, C.-C., & Carninci, P. (2020) · Nature · doi:10.1038/d41586-020-02139-1 · Cited by 10

Expanding studies of chromosome structure and function in the era of T2T genomics

Miga, K. H., & Sullivan, B. A. (2021) · Human Molecular Genetics · doi:10.1093/hmg/ddab214 · Cited by 11

Persistent spectral simplicial complex-based machine learning for chromosomal structural analysis in cellular differentiation

Gong, W., Wee, J., Wu, M.-C., Sun, X., Li, C., & Xia, K. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac168 · Cited by 10

High resolution discovery of chromatin interactions

Guo, Y., Krismer, K., Closser, M., Wichterle, H., & Gifford, D. K. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz051 · Cited by 10

Computational approaches for inferring 3D conformations of chromatin from chromosome conformation capture data

Meluzzi, D., & Arya, G. (2019) · Methods · doi:10.1016/j.ymeth.2019.08.008 · Cited by 10

HiCAR: a robust and sensitive multi-omic co-assay for simultaneous measurement of transcriptome, chromatin accessibility, and cis-regulatory chromatin contactsPreprint

Wei, X., Xiang, Y., Abnousi, A., Sun, T., Lin, X., Li, W., Hu, M., & Diao, Y.-R. (2020) · bioRxiv · doi:10.1101/2020.11.02.366062

KMT2D haploinsufficiency in Kabuki syndrome disrupts neuronal function through transcriptional and chromatin rewiring independent of H3K4-monomethylationPreprint

Gabriele, M., Vitriolo, A., Cuvertino, S., Pereira, M. F., Franconi, C., Germain, P., Capocefalo, D., Castaldi, D., Tenderini, E., Bèchet, N. B., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.04.22.440945 · Cited by 10

Peak-agnostic high-resolution cis-regulatory circuitry mapping using single cell multiome data

Zhang, Z., Ruf-Zamojski, F. M., Zamojski, M., Bernard, D. J., Chen, X. X., Troyanskaya, O. G., & Sealfon, S. C. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1166 · Cited by 9

CTPredictor: A comprehensive and robust framework for predicting cell types by integrating multi-scale features from single-cell Hi-C data

Shi, Z., & Wu, H. (2024) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2024.108336 · Cited by 9

Impact of Chromatin Organization and Epigenetics on CRISPR-Cas and TALEN Genome Editing

Jain, S., Xun, G., & Zhao, H. (2024) · ACS Synthetic Biology · doi:10.1021/acssynbio.4c00099 · Cited by 9

PU.1 eviction at lymphocyte-specific chromatin domains mediates glucocorticoid response in acute lymphoblastic leukemia

Beck, D., Cao, H., Tian, F., Huang, Y., Jiang, M., Zhao, H., Tai, X., Xu, W., Kosasih, H. J., Kealy, D. J., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-54096-2 · Cited by 9

CRISPR live-cell imaging reveals chromatin dynamics and enhancer interactions at multiple non-repetitive loci

Liu, M., Huang, K., Zhang, J., Li, Q., Wang, X., Gu, B.-M., Tang, H., Du, Z., Hu, L., Qi, S., et al. (2025) · Nature Biotechnology · doi:10.1038/s41587-025-02887-3 · Cited by 13

Communicating Genome Architecture: Biovisualization of the Genome, from Data Analysis and Hypothesis Generation to Communication and Learning

Goodstadt, M. N., & Martı́-Renom, M. A. (2018) · Journal of Molecular Biology · doi:10.1016/j.jmb.2018.11.008 · Cited by 10

The power of weak, transient interactions across biology: A paradigm of emergent behavior

Vásquez, P. A., Walker, B., Bloom, K., Kolbin, D., Caughman, N., Freeman, R., Lysy, M., Hult, C., Newhall, K. A., Papanikolas, M., et al. (2023) · Physica D Nonlinear Phenomena · doi:10.1016/j.physd.2023.133866 · Cited by 10

normGAM: an R package to remove systematic biases in genome architecture mapping data

Liu, T., & Wang, Z. (2019) · BMC Genomics · doi:10.1186/s12864-019-6331-8 · Cited by 9

Multi-omics annotation of human long non-coding RNAs

Li, Q., Zhao, L., Feng, C., Jiang, S., Zhang, Z., & Ma, L. (2020) · Biochemical Society Transactions · doi:10.1042/bst20191063 · Cited by 9

New Breeding Techniques: Detection and Identification of the Techniques and Derived Products

Bertheau, Y. (2018) · Elsevier eBooks · doi:10.1016/b978-0-08-100596-5.21834-9 · Cited by 10

Delayed DNA replication in haploid human embryonic stem cellsPreprint

Edwards, M. M., Zuccaro, M. V., Sagi, I., Ding, Q., Vershkov, D., Benvenisty, N., Egli, D. M., & Koren, A. (2021) · Genome Research · doi:10.1101/gr.275953.121 · Cited by 9

Mechanistic insights into the evolution of the differential expression of tandemly arrayed cone opsin genes in zebrafish

Tsujimura, T. (2020) · Development Growth & Differentiation · doi:10.1111/dgd.12690 · Cited by 8

Virtual reality inspection of chromatin 3D and 2D data

Molina, E., Kouřil, D., Tobias Isenberg, A., Kozlíková, B., & Vázquez, P. (2024) · Computers & Graphics · doi:10.1016/j.cag.2024.104059 · Cited by 8

Recipes and ingredients for deep learning models of 3D genome folding

Smaruj, P. N., Xiao, Y., & Fudenberg, G. (2025) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2024.102308 · Cited by 8

WashU Epigenome Browser update 2025

Seng, C., Liu, S., Zhang, W., Zhuo, X., Li, D., & Wang, T. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf387 · Cited by 10

An improved 4′-aminomethyltrioxsalen-based nucleic acid crosslinker for biotinylation of double-stranded DNA or RNA

Wielenberg, K., Wang, M., Yang, M., Ozer, A., Lis, J. T., & Lin, H. (2020) · RSC Advances · doi:10.1039/d0ra07437c · Cited by 8

Mapping nucleosome and chromatin architectures: A survey of computational methods

Fang, K., Wang, J., Liu, L., & Jin, V. X. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.07.037 · Cited by 9

Identifying TAD-like domains on single-cell Hi-C data by graph embedding and changepoint detection

Liu, E., Lyu, H., Liu, Y., Fu, L., Cheng, X., & Yin, X. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae138 · Cited by 8

Unveiling the role of chromosome structure morphology on gene function through chromosome conformation analysis

Zhan, Y., Yıldırım, A., Boninsegna, L., & Alber, F. (2025) · Genome biology · doi:10.1186/s13059-024-03472-8 · Cited by 8

Encounters in Three Dimensions: How Nuclear Topology Shapes Genome Integrity

Sebastian, R., Aladjem, M. I., & Oberdoerffer, P. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.746380 · Cited by 8

Mapping the nuclear landscape with multiplexed super-resolution fluorescence microscopy

Rahman, F., Augoustides, V., Tyler, E., Daugird, T. A., Arthur, C., & Legant, W. R. (2025) · Nature Communications · doi:10.1038/s41467-025-61358-0 · Cited by 9

Disrupted chromatin architecture in olfactory sensory neurons: looking for the link from COVID-19 infection to anosmia

Tan, Z. W., Toong, P. J., Guarnera, E., & Berezovsky, I. N. (2023) · Scientific Reports · doi:10.1038/s41598-023-32896-8 · Cited by 7

Bayesian methods in integrative structure modeling

Habeck, M. (2023) · Biological Chemistry · doi:10.1515/hsz-2023-0145 · Cited by 8

Pattern recognition in the landscape of seemingly random chimeric transcripts

Sridhar, A., More, A. S., Jadhav, A. R., Patil, K., Mavlankar, A., Dixit, V. M., & Bapat, S. A. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.10.028 · Cited by 7

Accelerating 3D genomics data analysis with Microcket

Zhao, Y. F., Yang, M., Gong, F., Pan, Y., Hu, M., Qin, P., Lu, L., Lyu, X., & Sun, K. (2024) · Communications Biology · doi:10.1038/s42003-024-06382-4 · Cited by 6

ChromEMT: visualizing and reconstructing chromatin ultrastructure and 3D organization in situ

Ou, H. D., Phan, S., Deerinck, T. J., Inagaki, A., Ellisman, M. H., & O’Shea, C. C. (2024) · Nature Protocols · doi:10.1038/s41596-024-01071-2 · Cited by 7

Two-Color Imaging of Nonrepetitive Endogenous Loci in Human Cells

Tasan, I., Su, C. J., Enghiad, B., Zhang, M., Mishra, S., & Zhao, H. (2020) · ACS Synthetic Biology · doi:10.1021/acssynbio.0c00295 · Cited by 7

GAMIBHEAR: whole-genome haplotype reconstruction from Genome Architecture Mapping data

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