Determinants of transcription factor regulatory range
Open accessPublished version of a preprint
Abstract
Characterization of the genomic distances over which transcription factor (TF) binding influences gene expression is important for inferring target genes from TF chromatin immunoprecipitation followed by sequencing (ChIP-seq) data. Here we systematically examine the relationship between thousands of TF and histone modification ChIP-seq data sets with thousands of gene expression profiles. We develop a model for integrating these data, which reveals two classes of TFs with distinct ranges of regulatory influence, chromatin-binding preferences, and auto-regulatory properties. We find that the regulatory range of the same TF bound within different topologically associating domains (TADs) depend on intrinsic TAD properties such as local gene density and G/C content, but also on the TAD chromatin states. Our results suggest that considering TF type, binding distance to gene locus, as well as chromatin context is important in identifying implicated TFs from GWAS SNPs.
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
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?
Chen et al. previously systematically integrated thousands of transcription factor binding and histone modification profiles assayed by ChIP-seq with thousands of gene expression profiles to identify two classes of transcription factors with distinct ranges of regulatory influence.
“Chen et al. previously systematically integrated thousands of transcription factor binding and histone modification profiles assayed by chromatin immunoprecipitation sequencing (ChIP-seq) with thousands of gene expression profiles to identify two classes of transcription factors with distinct ranges of regulatory influence31.”
From Transfer learning enables predictions in network biology (2023) · cites this paper as [31]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Model-based Analysis of ChIP-Seq (MACS)
Zhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., et al. (2008) · Genome Biology · doi:10.1186/gb-2008-9-9-r137 · Cited by 18,386 · see citing works
Self-citationAn integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072 · see citing works
Heinz, S., Benner, C., Spann, N., Bertolino, E., Lin, Y. C., Laslo, P., Cheng, J. X., Murre, C., Singh, H., & Glass, C. K. (2010) · Molecular Cell · doi:10.1016/j.molcel.2010.05.004 · Cited by 13,382 · see citing works
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 · see citing works
The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity
Barretina, J., Caponigro, G., Stransky, N., Venkatesan, K., Margolin, A. A., Kim, S., Wilson, C. J., Lehár, J., Kryukov, G. V., Sonkin, D., et al. (2012) · Nature · doi:10.1038/nature11003 · Cited by 7,950 · see citing works
High-Resolution Profiling of Histone Methylations in the Human Genome
Barski, A., Cuddapah, S., Cui, K., Roh, T.-Y., Schones, D. E., Wang, Z., Wei, G., Chepelev, I., & Zhao, K. (2007) · Cell · doi:10.1016/j.cell.2007.05.009 · Cited by 6,845 · see citing works
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 · see citing works
Self-citationThe International HapMap Project
†The International HapMap Consortium, Genotyping centres: Baylor College of Medicine and ParAllele BioScience, Gibbs, R. A., Belmont, J. W., Hardenbol, P., Willis, T. D., Yu, F., Chinese HapMap Consortium, Yang, H., Ch'ang, L.-Y., et al. (2003) · Nature · doi:10.1038/nature02168 · Cited by 6,057 · see citing works
Genome-wide maps of chromatin state in pluripotent and lineage-committed cells
Mikkelsen, T. S., Ku, M., Jaffe, D. B., Issac, B., Lieberman, E., Giannoukos, G., Alvarez, P., Brockman, W., Kim, T.-K., Koche, R. P., et al. (2007) · Nature · doi:10.1038/nature06008 · Cited by 4,129 · see citing works
Genome-Wide Mapping of in Vivo Protein-DNA Interactions
Johnson, D. S., Mortazavi, A., Myers, R. M., & Wold, B. (2007) · Science · doi:10.1126/science.1141319 · Cited by 2,927 · see citing works
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 · see citing works
Measuring and testing dependence by correlation of distances
Székely, G. J., Rizzo, M. L., & Bakirov, N. K. (2007) · The Annals of Statistics · doi:10.1214/009053607000000505 · Cited by 2,684 · see citing works
Piñero, J., Bravo, À., Queralt-Rosinach, N., Gutiérrez-Sacristán, A., Deu-Pons, J., Centeno, E., García-García, J., Sanz, F., & Furlong, L. I. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw943 · Cited by 2,680 · see citing works
An atlas of active enhancers across human cell types and tissues
The FANTOM Consortium, Andersson, R., Gebhard, C., Miguel-Escalada, I., Hoof, I., Bornholdt, J., Boyd, M., Chen, Y., Zhao, X., Schmidl, C., et al. (2014) · Nature · doi:10.1038/nature12787 · Cited by 2,550 · see citing works
A unique chromatin signature uncovers early developmental enhancers in humans
Rada-Iglesias, A., Bajpai, R., Swigut, T., Brugmann, S. A., Flynn, R. A., & Wysocka, J. (2011) · Nature · doi:10.1038/nature09692 · Cited by 2,233 · see citing works
The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog)
MacArthur, J., Bowler, E., Cerezo, M., Gil, L., Hall, P., Hastings, E., Junkins, H., McMahon, A., Milano, A., Morales, J., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1133 · Cited by 2,161 · see citing works
Genetic and epigenetic fine mapping of causal autoimmune disease variants
Farh, K. K.-H., Marson, A., Zhu, J., Kleinewietfeld, M., Housley, W. J., Beik, S., Shoresh, N., Whitton, H., Ryan, R. J. H., Shishkin, A. A., et al. (2015) · Nature · doi:10.1038/nature13835 · Cited by 1,956 · see citing works
The NIH Roadmap Epigenomics Mapping Consortium
Bernstein, B. E., Stamatoyannopoulos, J. A., Costello, J. F., Ren, B., Milosavljevic, A., Meissner, A., Kellis, M., Marra, M. A., Beaudet, A. L., Ecker, J. R., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt1010-1045 · Cited by 1,892 · see citing works
Phase separation drives heterochromatin domain formation
Strom, A. R., Emelyanov, A. V., Mir, M., Fyodorov, D. V., Darzacq, X., & Karpen, G. H. (2017) · Nature · doi:10.1038/nature22989 · Cited by 1,813 · see citing works
Chromatin architecture reorganization during stem cell differentiation
Dixon, J. R., Jung, I., Selvaraj, S., Shen, Y., Antosiewicz-Bourget, J. E., Lee, A. Y., Ye, Z., Kim, A., Rajagopal, N., Xie, W., et al. (2015) · Nature · doi:10.1038/nature14222 · Cited by 1,646 · see citing works
Pioneer transcription factors: establishing competence for gene expression
Zaret, K. S., & Carroll, J. S. (2011) · Genes & Development · doi:10.1101/gad.176826.111 · Cited by 1,589 · see citing works
Liquid droplet formation by HP1α suggests a role for phase separation in heterochromatin
Larson, A. G., Elnatan, D., Keenen, M. M., Trnka, M., Johnston, J. B., Burlingame, A., Agard, D., Redding, S., & Narlikar, G. J. (2017) · Nature · doi:10.1038/nature22822 · Cited by 1,554 · see citing works
Robertson, G., Hirst, M., Bainbridge, M., Bilenky, M., Zhao, Y., Zeng, T., Euskirchen, G., Bernier, B., Varhol, R., Delaney, A., et al. (2007) · Nature Methods · doi:10.1038/nmeth1068 · Cited by 1,454 · see citing works
Banerji, J., Olson, L., & Schaffner, W. (1983) · Cell · doi:10.1016/0092-8674(83)90015-6 · Cited by 1,407 · see citing works
Gillies, S. D., Morrison, S. L., Oi, V. T., & Tonegawa, S. (1983) · Cell · doi:10.1016/0092-8674(83)90014-4 · Cited by 1,361 · see citing works
Insulator dysfunction and oncogene activation in IDH mutant gliomas
Flavahan, W. A., Drier, Y., Liau, B. B., Gillespie, S. M., Venteicher, A. S., Stemmer-Rachamimov, A. O., Suvà, M. L., & Bernstein, B. E. (2016) · Nature · doi:10.1038/nature16490 · Cited by 1,288 · see citing works
Understanding mechanisms underlying human gene expression variation with RNA sequencing
Pickrell, J. K., Marioni, J. C., Pai, A. A., Degner, J. F., Engelhardt, B. E., Nkadori, E., Veyrieras, J.-B., Stephens, M., Gilad, Y., & Pritchard, J. K. (2010) · Nature · doi:10.1038/nature08872 · Cited by 1,256 · see citing works
Promoter-proximal pausing of RNA polymerase II: emerging roles in metazoans
Adelman, K., & Lis, J. T. (2012) · Nature Reviews Genetics · doi:10.1038/nrg3293 · Cited by 1,186 · see citing works
Lamina-Associated Domains: Links with Chromosome Architecture, Heterochromatin, and Gene Repression
van Steensel, B., & Belmont, A. S. (2017) · Cell · doi:10.1016/j.cell.2017.04.022 · Cited by 1,140 · see citing works
Ever-Changing Landscapes: Transcriptional Enhancers in Development and Evolution
Long, H. K., Prescott, S. L., & Wysocka, J. (2016) · Cell · doi:10.1016/j.cell.2016.09.018 · Cited by 945 · see citing works
Topologically associating domains are stable units of replication-timing regulation
Pope, B. D., Ryba, T., Dileep, V., Yue, F., Wu, W.-S., Denas, O., Vera, D. L., Wang, Y., Hansen, R. S., Canfield, T. K., et al. (2014) · Nature · doi:10.1038/nature13986 · Cited by 902 · see citing works
Higher-Order Inter-chromosomal Hubs Shape 3D Genome Organization in the Nucleus
Quinodoz, S. A., Ollikainen, N., Tabak, B., Palla, A., Schmidt, J. M., Detmar, E., Lai, M. M., Shishkin, A. A., Bhat, P., Takei, Y., et al. (2018) · Cell · doi:10.1016/j.cell.2018.05.024 · Cited by 892 · see citing works
BCL11A enhancer dissection by Cas9-mediated in situ saturating mutagenesis
Canver, M. C., Smith, E. C., Sher, F., Pinello, L., Sanjana, N. E., Shalem, O., Chen, D. D., Schupp, P. G., Vinjamur, D. S., Garcia, S. P., et al. (2015) · Nature · doi:10.1038/nature15521 · Cited by 886 · see citing works
Correlating chemical sensitivity and basal gene expression reveals mechanism of action
Rees, M. G., Seashore-Ludlow, B. A., Cheah, J. H., Adams, D., Price, E. V., Gill, S., Javaid, S., Coletti, M. E., Jones, V., Bodycombe, N. E., et al. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1986 · Cited by 874 · see citing works
A compendium of chromatin contact maps reveals spatially active regions in the human genome
Schmitt, A. D., Hu, M., Jung, I., Xu, Z., Qiu, Y., Tan, C. L., Li, Y., Lin, S., Lin, Y., Barr, C. L., et al. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.10.061 · Cited by 866 · see citing works
Going the Distance: A Current View of Enhancer Action
Blackwood, E. M., & Kadonaga, J. T. (1998) · Science · doi:10.1126/science.281.5373.60 · Cited by 836 · see citing works
Beyond GWASs: Illuminating the Dark Road from Association to Function
Edwards, S. L., Beesley, J., French, J. D., & Dunning, A. M. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.10.012 · Cited by 784 · see citing works
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., et al. (2017) · Nature · doi:10.1038/nature23884 · Cited by 732 · see citing works
Enhancer Control of Transcriptional Bursting
Fukaya, T., Lim, B., & Levine, M. (2016) · Cell · doi:10.1016/j.cell.2016.05.025 · Cited by 721 · see citing works
Linking disease associations with regulatory information in the human genomePreprint
Schaub, M. A., Boyle, A. P., Kundaje, A. B., Batzoglou, S., & Snyder, M. P. (2012) · Genome Research · doi:10.1101/gr.136127.111 · Cited by 715 · see citing works
Wang, Q., Li, W., Liu, X. S., Carroll, J. S., Jänne, O. A., Keeton, E. K., Chinnaiyan, A. M., Pienta, K. J., & Brown, M. A. (2007) · Molecular Cell · doi:10.1016/j.molcel.2007.05.041 · Cited by 689 · see citing works
Self-citationLiquid Nuclear Condensates Mechanically Sense and Restructure the Genome
Shin, Y., Chang, Y.-C., Lee, D. S. W., Berry, J., Sanders, D. W., Ronceray, P., Wingreen, N. S., Haataja, M., & Brangwynne, C. P. (2018) · Cell · doi:10.1016/j.cell.2018.10.057 · Cited by 676 · see citing works
Systematic mapping of functional enhancer–promoter connections with CRISPR interference
Fulco, C. P., Munschauer, M., Anyoha, R., Munson, G., Grossman, S. R., Perez, E. M., Kane, M., Cleary, B., Lander, E. S., & Engreitz, J. M. (2016) · Science · doi:10.1126/science.aag2445 · Cited by 643 · see citing works
Enhancer redundancy provides phenotypic robustness in mammalian development
Osterwalder, M., Barozzi, I., Tissières, V., Fukuda-Yuzawa, Y., Mannion, B. J., Afzal, S. Y., Lee, E. A., Zhu, Y., Plajzer-Frick, I., Pickle, C. S., et al. (2018) · Nature · doi:10.1038/nature25461 · Cited by 642 · see citing works
Recruitment to the Nuclear Periphery Can Alter Expression of Genes in Human Cells
Finlan, L. E., Sproul, D., Thomson, I., Boyle, S., Kerr, E. A., Perry, P., Ylstra, B., Chubb, J. R., & Bickmore, W. A. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000039 · Cited by 584 · see citing works
Chromatin marks identify critical cell types for fine mapping complex trait variants
Trynka, G., Sandor, C., Han, B., Xu, H., Stranger, B. E., Liu, X. S., & Raychaudhuri, S. (2013) · Nature Genetics · doi:10.1038/ng.2504 · Cited by 580 · see citing works
Self-citationMei, S., Qin, Q., Wu, Q., Sun, H., Zheng, R., Zang, C., Zhu, M., Wu, J., Shi, X., Taing, L., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw983 · Cited by 571 · see citing works
Self-citationTarget analysis by integration of transcriptome and ChIP-seq data with BETA
Wang, S., Sun, H., Ma, J., Zang, C., Wang, C., Wang, J., Tang, Q., Meyer, C. A., Zhang, Y., & Liu, X. S. (2013) · Nature Protocols · doi:10.1038/nprot.2013.150 · Cited by 544 · see citing works
Self-citationPetryszak, R., Keays, M., Tang, A., Fonseca, N. A., Barrera, E., Burdett, T., Füllgrabe, A., Fuentes, A. M.-P., Jupp, S., Koskinen, S., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1045 · Cited by 530 · see citing works
The rise and fall of Hox gene clusters
Duboule, D. (2007) · Development · doi:10.1242/dev.001065 · Cited by 525 · see citing works
Mumbach, M. R., Satpathy, A. T., Boyle, E. A., Dai, C., Gowen, B. G., Cho, S. W., Nguyen, M. L., Rubin, A. J., Granja, J. M., Kazane, K. R., et al. (2017) · Nature Genetics · doi:10.1038/ng.3963 · Cited by 490 · see citing works
Perinuclear localization of chromatin facilitates transcriptional silencing
Andrulis, E. D., Neiman, A. M., Zappulla, D. C., & Sternglanz, R. (1998) · Nature · doi:10.1038/29100 · Cited by 468 · see citing works
The Genetics of Transcription Factor DNA Binding Variation
Deplancke, B., Alpern, D., & Gardeux, V. (2016) · Cell · doi:10.1016/j.cell.2016.07.012 · Cited by 390 · see citing works
Seipel, K., Georgiev, O., & Schaffner, W. (1992) · The EMBO Journal · doi:10.1002/j.1460-2075.1992.tb05603.x · Cited by 359 · see citing works
Highly rearranged chromosomes reveal uncoupling between genome topology and gene expression
Ghavi-Helm, Y., Jankowski, A., Meiers, S., Viales, R. R., Korbel, J. O., & Furlong, E. E. M. (2019) · Nature Genetics · doi:10.1038/s41588-019-0462-3 · Cited by 354 · see citing works
Genome‐wide meta‐analysis identifies novel multiple sclerosis susceptibility loci
Patsopoulos, N. A., the Bayer Pharma MS Genetics Working Group, T. S. C. O. S. E. I. A. A. C., & de Bakker, P. I. W. (2011) · Annals of Neurology · doi:10.1002/ana.22609 · Cited by 353 · see citing works
Live-cell imaging reveals enhancer-dependent Sox2 transcription in the absence of enhancer proximity
Alexander, J. M., Guan, J., Li, B., Maliskova, L., Song, M., Shen, Y., Huang, B., Lomvardas, S., & Weiner, O. D. (2019) · eLife · doi:10.7554/elife.41769 · Cited by 346 · see citing works
Gene expression analyses reveal molecular relationships among 20 regions of the human CNS
Roth, R. B., Hevezi, P. A., Lee, J. S. H., Willhite, D., Lechner, S. M., Foster, A. C., & Zlotnik, A. (2006) · Neurogenetics · doi:10.1007/s10048-006-0032-6 · Cited by 342 · see citing works
Type 2 Diabetes and Subsequent Incidence of Breast Cancer in the Nurses’ Health Study
Michels, K. B., Solomon, C. G., Hu, F. B., ROSNER, B. A., Hankinson, S. E., Colditz, G. A., & Manson, J. E. (2003) · Diabetes Care · doi:10.2337/diacare.26.6.1752 · Cited by 341 · see citing works
Ouyang, Z., Zhou, Q., & Wong, W. H. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0904863106 · Cited by 329 · see citing works
Diabetes and pancreatic cancer
Li, D. (2011) · Molecular Carcinogenesis · doi:10.1002/mc.20771 · Cited by 315 · see citing works
Isoda, T., Moore, A. J., He, Z., Chandra, V. K., Aida, M., Denholtz, M., van Hamburg, J. P., Fisch, K. M., Chang, A. N., Fahl, S. P., et al. (2017) · Cell · doi:10.1016/j.cell.2017.09.001 · Cited by 311 · see citing works
Three Functional Classes of Transcriptional Activation Domains
Blau, J., Xiao, H., McCracken, S. A., O’Hare, P., Greenblatt, J., & Bentley, D. L. (1996) · Molecular and Cellular Biology · doi:10.1128/mcb.16.5.2044 · Cited by 268 · see citing works
The Genotype-Tissue Expression (GTEx) project
Lonsdale, J., Thomas, J., Salvatore, M., Phillips, R., Lo, E., Shad, S., Hasz, R., Walters, G., Garcia, F., Young, N., et al. (2013) · Nature Genetics · doi:10.1038/ng.2653 · Cited by 263 · see citing works
Ge, X., Yamamoto, S., Tsutsumi, S., Midorikawa, Y., Ihara, S., Wang, S. M., & Aburatani, H. (2005) · Genomics · doi:10.1016/j.ygeno.2005.04.008 · Cited by 246 · see citing works
Symmons, O., Pan, L., Remeseiro, S., Aktas, T., Klein, F., Huber, W., & Spitz, F. (2016) · Developmental Cell · doi:10.1016/j.devcel.2016.10.015 · Cited by 222 · see citing works
A unified architecture of transcriptional regulatory elements
Andersson, R., Sandelin, A., & Danko, C. G. (2015) · Trends in Genetics · doi:10.1016/j.tig.2015.05.007 · Cited by 211 · see citing works
Jia, L., Zhou, Z., Liang, H., Wu, J., Shi, P., Li, F., Wang, Z., Wang, C., Chen, W., Zhang, H., et al. (2015) · Oncogene · doi:10.1038/onc.2015.263 · Cited by 178 · see citing works
Self-citationSato, T., Kaneda, A., Tsuji, S., Isagawa, T., Yamamoto, S., Fujita, T., Yamanaka, R., Tanaka, Y., Nukiwa, T., Márquez, V. E., et al. (2013) · Scientific Reports · doi:10.1038/srep01911 · Cited by 177 · see citing works
Bagheri‐Fam, S., Barrionuevo, F. J., Dohrmann, U., Günther, T., Schüle, R., Kemler, R., Mallo, M., Kanzler, B., & Scherer, G. (2006) · Developmental Biology · doi:10.1016/j.ydbio.2005.11.013 · Cited by 165 · see citing works
Promoter-Intrinsic and Local Chromatin Features Determine Gene Repression in LADs
Leemans, C., van der Zwalm, M. C. H., Brueckner, L., Comoglio, F., van Schaik, T., Pagie, L., van Arensbergen, J., & van Steensel, B. (2019) · Cell · doi:10.1016/j.cell.2019.03.009 · Cited by 165 · see citing works
Saleh, S. A., Al‐Mulla, F., & Luqmani, Y. A. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020610 · Cited by 159 · see citing works
RNA polymerase II C-terminal domain required for enhancer-driven transcription
Gerber, H. P., Hagmann, M., Seipel, K., Georgiev, O., West, M. A. L., Litingtung, Y., Schaffner, W., & Corden, J. L. (1995) · Nature · doi:10.1038/374660a0 · Cited by 157 · see citing works
The Hierarchy of Transcriptional Activation: From Enhancer to Promoter
Vernimmen, D., & Bickmore, W. A. (2015) · Trends in Genetics · doi:10.1016/j.tig.2015.10.004 · Cited by 155 · see citing works
Jacobs, J., Atkins, M., Davie, K., Imrichova, H., Romanelli, L., Christiaens, V., Hulselmans, G., Potier, D., Wouters, J., Taskiran, I. I., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0140-x · Cited by 155 · see citing works
Targeted exploration and analysis of large cross-platform human transcriptomic compendia
Zhu, Q., Wong, A. K., Krishnan, A., Aure, M. R. R., Tadych, A., Zhang, R., Corney, D. C., Greene, C. S., Bongo, L. A., Kristensen, V. N., et al. (2015) · Nature Methods · doi:10.1038/nmeth.3249 · Cited by 149 · see citing works
Savić, N., Bär, D., Leone, S., Frommel, S. C., Weber, F. A., Vollenweider, E., Ferrari, E. S., Ziegler, U., Kaech, A., Shakhova, O., et al. (2014) · Cell stem cell · doi:10.1016/j.stem.2014.10.005 · Cited by 144 · see citing works
Chronic lymphocytic leukemia and autoimmunity: a systematic review
Hodgson, K. E., Ferrer, G., Montserrat, E., & Moreno, C. (2011) · Haematologica · doi:10.3324/haematol.2010.036152 · Cited by 144 · see citing works
Long-range downstream enhancers are essential for Pax6 expression
Kleinjan, D. A., Seawright, A., Mella, S., Carr, C. B., Tyas, D. A., Simpson, T. I., Mason, J. O., Price, D. J., & van Heyningen, V. (2006) · Developmental Biology · doi:10.1016/j.ydbio.2006.08.060 · Cited by 136 · see citing works
Bergamaschi, A., Madak‐Erdogan, Z., Kim, Y. J., Choi, Y., Lu, H., & Katzenellenbogen, B. S. (2014) · Breast Cancer Research · doi:10.1186/s13058-014-0436-4 · Cited by 130 · see citing works
Insulators and domains of gene expression
Ali, T., Renkawitz, R., & Bartkuhn, M. (2016) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2015.11.009 · Cited by 121 · see citing works
ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline
Qin, Q., Mei, S., Wu, Q., Sun, H., Li, L., Taing, L., Chen, S., Li, F., Liu, T., Zang, C., et al. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-1274-4 · Cited by 119 · see citing works
Self-citationTranscriptional autoregulation in development
Crews, S. T., & Pearson, J. C. (2009) · Current Biology · doi:10.1016/j.cub.2009.01.015 · Cited by 112 · see citing works
Novel c‐MYC target genes mediate differential effects on cell proliferation and migration
Cappellen, D., Schlange, T., Bauer, M., Maurer, F., & Hynes, N. E. (2006) · EMBO Reports · doi:10.1038/sj.embor.7400849 · Cited by 110 · see citing works
Repression of DNA-binding dependent glucocorticoid receptor-mediated gene expression
Muzikar, K. A., Nickols, N. G., & Dervan, P. B. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0909192106 · Cited by 101 · see citing works
Clusters of Conserved Beta Cell Marker Genes for Assessment of Beta Cell Phenotype
Martens, G. A., Jiang, L., Hellemans, K., Stangé, G. M., Heimberg, H., Nielsen, F. C., Sand, O., van Helden, J., Gorus, F., & PIPELEERS, D. G. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024134 · Cited by 93 · see citing works
Olofsson, L. E., Orho‐Melander, M., William‐Olsson, L., Sjöholm, K., Sjöström, L., Groop, L., Carlsson, B., Carlsson, L. M. S., & Olsson, B. (2008) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2008-0574 · Cited by 83 · see citing works
Role of RUNX in autoimmune diseases linking rheumatoid arthritis, psoriasis and lupus.
Alarcón-Riquelme, M. E. (2004) · Arthritis Research · doi:10.1186/ar1203 · Cited by 71 · see citing works
Dekker, J. (2007) · Genome biology · doi:10.1186/gb-2007-8-6-r116 · Cited by 68 · see citing works
Burwinkel, B., Shanmugam, K. S., Hemminki, K., Meindl, A., Schmutzler, R. K., Sutter, C., Wappenschmidt, B., Kiechle, M. B., Bartram, C. R., & Frank, B. (2006) · BMC Cancer · doi:10.1186/1471-2407-6-268 · Cited by 55 · see citing works
Dorris, D. R., & Struhl, K. (2000) · Molecular and Cellular Biology · doi:10.1128/mcb.20.12.4350-4358.2000 · Cited by 41 · see citing works
Palani, S., & Sarkar, C. A. (2008) · Biophysical Journal · doi:10.1529/biophysj.107.120600 · Cited by 39 · see citing works
DistiLD Database: diseases and traits in linkage disequilibrium blocks
Pallejá, A., Horn, H., Eliasson, S., & Jensen, L. J. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr899 · Cited by 35 · see citing works
Hosoya-Ohmura, S., Mizuno, S., Oishi, H., Ku, C.-J., Hermann, M., Hosoya, T., Takahashi, S., & Engel, J. D. (2016) · Journal of Clinical Investigation · doi:10.1172/jci83894 · Cited by 27 · see citing works
PARP mediated chromatin unfolding is coupled to long-range enhancer activationPreprint
Benabdallah, N. S., Williamson, I., Illingworth, R. S., Boyle, S., Grimes, G. R., Therizols, P., & Bickmore, W. A. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/155325 · Cited by 24 · see citing works
Live-Cell Imaging Reveals Enhancer-dependent Sox2 Transcription in the Absence of Enhancer ProximityPreprint
Alexander, J. M., Guan, J., Huang, B., Lomvardas, S., & Weiner, O. D. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/409672 · Cited by 20 · see citing works
Marsden, M. D., & Fournier, R. E. K. (2003) · Molecular and Cellular Biology · doi:10.1128/mcb.23.10.3516-3526.2003 · Cited by 17 · see citing works
TCF7L2 gene polymorphisms and susceptibility to breast cancer: a meta-analysis
Lu, X., Hu, G., Du, J. Q., & Li, H. Q. (2015) · Genetics and Molecular Research · doi:10.4238/2015.march.31.16 · Cited by 12 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Transfer learning enables predictions in network biology
Theodoris, C. V., Xiao, L., Chopra, A., Chaffin, M. D., Al Sayed, Z. R., Hill, M. C., Mantineo, H., Brydon, E. M., Zeng, Z., Liu, X. S., et al. (2023) · Nature · doi:10.1038/s41586-023-06139-9 · Cited by 1,193 · see citing works
Self-citationMechanisms of Interplay between Transcription Factors and the 3D Genome
Kim, S., & Shendure, J. (2019) · Molecular Cell · doi:10.1016/j.molcel.2019.08.010 · Cited by 204 · see citing works
Integrative analyses of single-cell transcriptome and regulome using MAESTRO
Wang, C., Sun, D., Huang, X., Wan, C., Li, Z., Han, Y., Qin, Q., Fan, J., Qiu, X., Xie, Y., et al. (2020) · Genome biology · doi:10.1186/s13059-020-02116-x · Cited by 183 · see citing works
Self-citationUniBind: maps of high-confidence direct TF-DNA interactions across nine species
Puig, R. R., Boddie, P., Khan, A., Castro-Mondragon, J. A., & Mathelier, A. (2021) · BMC Genomics · doi:10.1186/s12864-021-07760-6 · Cited by 102 · see citing works
MIRA: joint regulatory modeling of multimodal expression and chromatin accessibility in single cells
Lynch, A. W., Theodoris, C. V., Long, H. W., Brown, M., Liu, X. S., & Meyer, C. A. (2022) · Nature Methods · doi:10.1038/s41592-022-01595-z · Cited by 80 · see citing works
Self-citationTumor suppressor p53: from engaging DNA to target gene regulation
Sammons, M. A., Nguyen, T., McDade, S. S., & Fischer, M. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa666 · Cited by 77 · see citing works
Wen, Y., Dungan, C. M., Mobley, C. B., Valentino, T. R., von Walden, F., & Murach, K. A. (2021) · Function · doi:10.1093/function/zqab038 · Cited by 77 · see citing works
Cistrome Data Browser: integrated search, analysis and visualization of chromatin data
Taing, L., Dandawate, A., L’Yi, S., Gehlenborg, N., Brown, M. A., & Meyer, C. A. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1069 · Cited by 71 · see citing works
Self-citationZhang, G., Song, C., Yin, M., Liu, L., Zhang, Y., Li, Y., Zhang, J., Guo, M., & Li, C. (2025) · Nature Communications · doi:10.1038/s41467-025-58921-0 · Cited by 55 · see citing works
Spatial Features and Functional Implications of Plant 3D Genome Organization
Domb, K., Wang, N., Hummel, G., & Liu, C. (2022) · Annual Review of Plant Biology · doi:10.1146/annurev-arplant-102720-022810 · Cited by 53 · see citing works
Singh, R., Wu, A. P., Mudide, A., & Berger, B. (2024) · Cell Systems · doi:10.1016/j.cels.2024.04.005 · Cited by 34 · see citing works
Tuning up Transcription Factors for Therapy
Becskei, A. (2020) · Molecules · doi:10.3390/molecules25081902 · Cited by 27 · see citing works
RegVelo: Gene-regulatory-informed dynamics of single cells
Wang, W., Hu, Z., Weiler, P., Mayes, S., Lange, M., Fountain, D. M., Haug, J. O., Wang, J., Xue, Z., Sauka‐Spengler, T., et al. (2026) · Cell · doi:10.1016/j.cell.2026.04.022 · Cited by 26 · see citing works
Rundquist, O., Nestor, C. E., Jenmalm, M. C., Hellberg, S., & Gustafsson, M. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.835625 · Cited by 18 · see citing works
Ball, C. B., Li, M., Parida, M., Hu, Q., Ince, D., Collins, G., Meier, J. L., & Price, D. H. (2022) · mBio · doi:10.1128/mbio.00337-22 · Cited by 16 · see citing works
Parisutham, V., Chhabra, S., Ali, M. Z., & Brewster, R. C. (2022) · Molecular Systems Biology · doi:10.15252/msb.202110843 · Cited by 18 · see citing works
Deciphering the species-level structure of topologically associating domainsPreprint
Singh, R., & Berger, B. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.28.466333 · Cited by 14 · see citing works
Known allosteric proteins have central roles in genetic disease
Abrusán, G., Ascher, D. B., & Inouye, M. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009806 · Cited by 13 · see citing works
Active enhancers: recent research advances and insights into disease
Zhang, J., Wang, Q., Liu, J., Duan, Y., Liu, Z., Zhang, Z., & Li, C. (2024) · Biology Direct · doi:10.1186/s13062-024-00559-x · Cited by 13 · see citing works
Self-citationLiao, Z., Tang, S., Nozawa, K., Shimada, K., Ikawa, M., Monsivais, D., & Matzuk, M. M. (2024) · eLife · doi:10.7554/elife.91434.4 · Cited by 9 · see citing works
Molecular competition can shape enhancer activity in the Drosophila embryo
Waymack, R., Gad, M., & Wunderlich, Z. (2021) · iScience · doi:10.1016/j.isci.2021.103034 · Cited by 6 · see citing works
Unveiling causal regulatory mechanisms through cell-state parallax
Wu, A. P., Singh, R., Walsh, C. A., & Berger, B. (2025) · Nature Communications · doi:10.1038/s41467-025-61337-5 · Cited by 9 · see citing works
From bedside to bench: regulation of host factors in SARS-CoV-2 infection
Ong, S. Y. Q., Flyamer, I. M., Bickmore, W. A., & Biddie, S. C. (2021) · Experimental & Molecular Medicine · doi:10.1038/s12276-021-00595-x · Cited by 8 · see citing works
Cross-species cellular mapping and humanization of Fcγ receptors to advance antibody modeling
Damme, K. F. A. V., Sichien, D., der Borght, K. V., Moorleghem, J. V., Gassen, S. V., Jorssen, J., Winter, S. D., Leeuw, E. D., Wang, C., Chai, Q., et al. (2026) · Science Immunology · doi:10.1126/sciimmunol.ady7328 · Cited by 7 · see citing works
Chen, H., Venkatesh, M. S., Ortega, J. G., Mahesh, S. V., Nandi, T. N., Madduri, R., Pelka, K., & Theodoris, C. V. (2026) · Nature Computational Science · doi:10.1038/s43588-026-00972-4 · Cited by 10 · see citing works
Multimodal learning of noncoding variant effects using genome sequence and chromatin structure
Tan, W., & Shen, Y. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad541 · Cited by 7 · see citing works
Wang, S., Wang, Z., & Zang, C. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf015 · Cited by 7 · see citing works
Filtering of Data-Driven Gene Regulatory Networks Using Drosophila melanogaster as a Case Study
Cuesta-Astroz, Y., Rucatti, G. G., Saavedra, L. M., SanMartín, C. D., Sanhueza, M., & Martín, A. J. M. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.649764 · Cited by 7 · see citing works
scKGBERT: a knowledge-enhanced foundation model for single-cell transcriptomics
Li, Y. E., Qiao, G., Du, H., Gao, X., & Wang, G. (2025) · Genome biology · doi:10.1186/s13059-025-03862-6 · Cited by 6 · see citing works
Cell-GraphCompass: modeling single cells with graph structure foundation model
Fang, C., Cui, W., Hu, Z., Liu, W., Chen, S., Chang, S., Long, Q., Li, C., Liu, Y., Jiang, H., et al. (2025) · National Science Review · doi:10.1093/nsr/nwaf255 · Cited by 6 · see citing works
Annotating regulatory elements by heterogeneous network embedding
Lu, Y., Feng, Z., Zhang, S., & Wang, Y. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac185 · Cited by 5 · see citing works
How Do Large Language Models Understand Genes and Cells
Fang, C., Wang, Y., Song, Y., Long, Q., Wang, L., Chen, L.-H., Wang, P., Feng, G., Zhou, Y., & Li, X. (2024) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3702234 · Cited by 6 · see citing works
Evidence of widespread, independent sequence signature for transcription factor cobindingPreprint
Zhou, M., Li, H., Wang, X., & Guan, Y. (2020) · Genome Research · doi:10.1101/gr.267310.120 · Cited by 6 · see citing works
Ma, W., & Chaisson, M. (2025) · Nature Genetics · doi:10.1038/s41588-025-02346-4 · Cited by 5 · see citing works
He, J., Perera, D., Wen, W., Ping, J., Li, Q., Lyu, L., Chen, Z., Shu, X., Long, J., Cai, Q., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1035 · Cited by 5 · see citing works
Long-range massively parallel reporter assay reveals rules of distal enhancer-promoter interactionsPreprint
Wu, Y., Li, J., Bartley-Dier, E. L., Pitts, C., & Cohen, B. A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.04.21.649048 · Cited by 5 · see citing works
Jang, S., Yoon, S.-W., Yang, H.-J., Choi, N., Han, S.-H., Kim, L. K., Kim, H., Park, J. H., Lee, D., & Yoo, K. H. (2025) · 癌症：英文版 · doi:10.1002/cac2.70049 · Cited by 4 · see citing works
Buren, E. V., Zhang, Y., Li, X., Selvaraj, M. S., Li, Z., Zhou, H., Palmer, N. D., Arnett, D. K., Blangero, J., Boerwinkle, E., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02919-5 · Cited by 4 · see citing works
Liao, Z., Tang, S., Nozawa, K., Shimada, K., Ikawa, M., Monsivais, D., & Matzuk, M. M. (2023) · eLife · doi:10.7554/elife.91434 · Cited by 12 · see citing works
Swindell, W. R. (2024) · Frontiers in Genetics · doi:10.3389/fgene.2024.1385114 · Cited by 4 · see citing works
Morin, A. M., Chu, E. C.-P., Sharma, A., Adrian-Hamazaki, A., & Pavlidis, P. (2023) · Genome Research · doi:10.1101/gr.277273.122 · Cited by 4 · see citing works
Tahara, S., & Ozaki, H. (2025) · Briefings in Functional Genomics · doi:10.1093/bfgp/elaf016 · Cited by 3 · see citing works
Brown, M. A., Dodd, A., Shi, F., Greenwood, E., Nagpal, S., Kolachala, V. L., Kugathasan, S., & Gibson, G. C. (2024) · Journal of Crohn s and Colitis · doi:10.1093/ecco-jcc/jjae055 · Cited by 3 · see citing works
Self-citationPredicting Methods of Transcription Factor Binding Sites
Li, D., Liu, Z., Chen, X. X., Yang, Y., Lv, X., Li, X., & Shi, Q. (2021) · International Conference on Computational Intelligence and Security (CIS) · doi:10.1109/cis54983.2021.00021 · Cited by 3 · see citing works
Liu, Q., Zeng, W., Hongtu Zhu, B., Li, L., Wong, W. H., & Initiative, A. D. N. (2024) · medRxiv · doi:10.1101/2024.10.03.24314824 · Cited by 3 · see citing works
Data enhancement in the age of spatial biology
Liao, L., Martin, P. C. N., Kim, H., Panahandeh, S., & Won, K. (2024) · Advances in cancer research · doi:10.1016/bs.acr.2024.06.008 · Cited by 2 · see citing works
Gong, X., Li, J., Yan, Z., Sun, A., Zheng, Y., Yin, M., Xiao, Q., & Liu, Z. (2025) · Plants · doi:10.3390/plants14111701 · Cited by 2 · see citing works
Wang, Z., Wang, S., & Zang, C. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.06.18.545510 · Cited by 2 · see citing works
Mousavi, Z., Arvanitis, M., Duong, T., Brody, J. A., Battle, A. J., Sotoodehnia, N., Shojaie, A., Arking, D. E., & Bader, J. S. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012725 · Cited by 1 · see citing works
Computational Approaches to Modeling Transcription Factor Activity and Gene Regulation
Meyer, C. A., & Liu, X. S. (2020) · Trends in Biochemical Sciences · doi:10.1016/j.tibs.2020.09.005 · Cited by 1 · see citing works
Self-citationLi, J., Xu, W., Zhong, Y., Jing, G., Wang, T., Fu, F., & Wang, G. (2024) · Industrial Crops and Products · doi:10.1016/j.indcrop.2024.118597 · Cited by 1 · see citing works
Labani, M., Beheshti, A., & O'Brien, T. A. (2024) · Genes · doi:10.3390/genes15070938 · Cited by 1 · see citing works
Uncovering Potential Novel Biomarkers In Crohn's Disease Using Integrated Bioinformatics AnalysisPreprint
Feng, J. (2022) · Research Square · doi:10.21203/rs.3.rs-1301164/v1 · Cited by 1 · see citing works
Morin, A. M., Chu, E. C.-P., Sharma, A., Adrian-Hamazaki, A., & Pavlidis, P. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.30.505909 · Cited by 1 · see citing works
Liao, Z., Tang, S., Nozawa, K., Shimada, K., Ikawa, M., Monsivais, D., & Matzuk, M. M. (2024) · eLife · doi:10.7554/elife.91434.2 · Cited by 1 · see citing works
scKEPLM: Knowledge enhanced large-scale pre-trained language model for single-cell transcriptomicsPreprint
Li, Y., Qiao, G., & Wang, G. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.09.602633 · Cited by 1 · see citing works
Parisutham, V., Chhabra, S., Ali, M. Z., & Brewster, R. C. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.16.468742
Rundquist, O. (2021) · Linköping studies in science and technology. Dissertations · doi:10.3384/9789179291044
Uncovering potential novel biomarkers in Crohn's disease using integrated bioinformatics analysisPreprint
Feng, J. (2022) · Research Square · doi:10.21203/rs.3.rs-1301164/v2
Multimodal learning of noncoding variant effects using genome sequence and chromatin structurePreprint
Tan, W., & Shen, Y. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.20.521331
Predicting Algorithm of Transcription Factor Binding Sites Based on Weighted Multi-Grained Scanning
Liu, Z., Li, D., Chen, X., Lv, X., Zhu, D., & Li, X. (2022) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm55620.2022.9995630
OGRE: calculate, visualize, and analyze overlap between genomic input regions and public annotations
Berres, S., Gromoll, J., Wöste, M., Sandmann, S., & Laurentino, S. (2023) · BMC Bioinformatics · doi:10.1186/s12859-023-05422-w
Liao, Z., Tang, S., Nozawa, K., Shimada, K., Ikawa, M., Monsivais, D., & Matzuk, M. M. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.09.25.559321
Liao, Z., Tang, S., Nozawa, K., Shimada, K., Ikawa, M., Monsivais, D., & Matzuk, M. M. (2023) · eLife · doi:10.7554/elife.91434.1
Liao, Z., Tang, S., Nozawa, K., Shimada, K., Ikawa, M., Monsivais, D., & Matzuk, M. M. (2024) · eLife · doi:10.7554/elife.91434.2.sa4
Liao, Z., Tang, S., Nozawa, K., Shimada, K., Ikawa, M., Monsivais, D., & Matzuk, M. M. (2024) · eLife · doi:10.7554/elife.91434.3
Berres, S., Gromoll, J., Wöste, M., Sandmann, S., & Laurentino, S. (2023) · Figshare · doi:10.6084/m9.figshare.23788235
Berres, S., Gromoll, J., Wöste, M., Sandmann, S., & Laurentino, S. (2023) · Figshare · doi:10.6084/m9.figshare.23788250
Berres, S., Gromoll, J., Wöste, M., Sandmann, S., & Laurentino, S. (2023) · Figshare · doi:10.6084/m9.figshare.23788247
Brown, M. A., Ferrari, A., Dodd, A., Fang, S., Kolachala, V. L., Kugathasan, S., Wolfinger, R. D., & Gibson, G. C. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.25.666784
Self-citationAltered histone modifications in Aedes aegypti following Rift Valley fever virus exposurePreprint
Ogg, H. A., Mikol, Z. M., King, D. C., Mire, C. E., Arhouma, Z., Nishimura, E. O., Kading, R. C., & Campbell, C. L. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.11.675494
p53motifDB: integration of genomic information and tumour suppressor p53 binding motifs
Baniulyte, G., Hicks, S. M., & Sammons, M. A. (2025) · Database · doi:10.1093/database/baaf053
Pillai, M., & Amaral, L. A. N. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.09.25.678593
The Binding Landscape of an Essential Nuclear Hormone Receptor in C. elegansPreprint
Sinks, A. L., Asahina, M., Yamamoto, K. R., Ward, J. D., & Thurtle-Schmidt, D. M. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2025.12.14.694179
Berres, S., Gromoll, J., Wöste, M., Sandmann, S., & Laurentino, S. (2023) · Figshare · doi:10.6084/m9.figshare.23788244
Additional file 1 of UniBind: maps of high-confidence direct TF-DNA interactions across nine species
Puig, R. R., Boddie, P., Khan, A., Castro-Mondragon, J. A., & Mathelier, A. (2021) · Figshare · doi:10.6084/m9.figshare.14853540
Berres, S., Gromoll, J., Wöste, M., Sandmann, S., & Laurentino, S. (2023) · Figshare · doi:10.6084/m9.figshare.23788238
Berres, S., Gromoll, J., Wöste, M., Sandmann, S., & Laurentino, S. (2023) · Figshare · doi:10.6084/m9.figshare.23788241
Altered histone modifications in Aedes aegypti midguts following Rift Valley fever virus exposure
Ogg, H. A., Mikol, Z. M., King, D. C., Mire, C. E., Arhouma, Z., Nishimura, E. O., Kading, R. C., & Campbell, C. L. (2026) · Scientific Reports · doi:10.1038/s41598-026-37729-y
Decomposing multi-scale dynamic regulation from single-cell multiomics with scMagnifyPreprint
Chen, X., Yan, X., Shen, B., Wang, H., Tang, Z., Zang, Y., Lin, P., Zhang, H., Li, Y., & Li, H. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.02.03.703669
Gènes cibles des hormones thyroïdiennes, un regard nouveau par le prisme des analyses pangénomiques
Zekri, Y. (2022) · theses.fr (ABES) · doi:10.70675/f8d646ffzf184z40e1z848az174a3d652f5d
Henchy, C., Wang, H., & Prochownik, E. V. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.22.733817
de Melo, D. G., Rodrigues, V. C. D. C., & de Moura, L. P. (2026) · Next research. · doi:10.1016/j.nexres.2026.102120
TNFAIP3/A20 dysfunction drives innate and sterile hyperinflammation
Damme, K. F. A. V., Hertens, P., Sichien, D., der Borght, K. V., Moorleghem, J. V., Prijck, S. D., Klarenbeek, A., Louagie, E., Lammens, I., Vanhee, S., et al. (2026) · Frontiers in Immunology · doi:10.3389/fimmu.2026.1856810
- Authors
- Chen, C.-H., Zheng, R., Tokheim, C., Dong, X., Fan, J., Wan, C., Tang, Q., Brown, M., Liu, J. S., Meyer, C. A., & Liu, X. S.
- Affiliations
- Harvard University (US)
- Tongji University (CN)
- Corresponding author
- Meyer, Clifford A.
- Liu, X. Shirley
- ORCID
- Venue
- Nature Communications
- Published
- 2020-05-18
- Volume
- 11
- Issue
- 1
- Pages
- 2472-2472
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC7235260
- OpenAlex
- W3024498749
- Cited by
- 85
- References
- 98
- Citations by year
- 2026: 8 · 2025: 17 · 2024: 18 · 2023: 12 · 2022: 13 · 2021: 11 · 2020: 5 · 2019: 1
- FWCI
- 3.57
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (U24 HG009446)
- 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 › Genetics › Genetic Associations and Epidemiology
- Keywords
- topologically associating domains, chromatin state, histone modifications, gene expression, autoregulation, GWAS SNPs, gene density, GC content
- MeSH terms
- Acetylation, Animals, Cell Line, Chromatin, Gene Expression Regulation, Histones, Lysine, Models, Genetic, Protein Binding, Transcription Factors, Polymorphism, Single Nucleotide, Transcription Initiation Site, Quantitative Trait Loci, Mice, Genome-Wide Association Study
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
