The DOI matches its Crossref record; 52 of the 53 references it cites were found in a registry or an index.
The Ensembl Regulatory Build
Open accessAbstract
Most genomic variants associated with phenotypic traits or disease do not fall within gene coding regions, but in regulatory regions, rendering their interpretation difficult. We collected public data on epigenetic marks and transcription factor binding in human cell types and used it to construct an intuitive summary of regulatory regions in the human genome. We verified it against independent assays for sensitivity. The Ensembl Regulatory Build will be progressively enriched when more data is made available. It is freely available on the Ensembl browser, from the Ensembl Regulation MySQL database server and in a dedicated track hub.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures



Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“restricting to Alzheimer’s disease–relevant tissues (via Ensembl Regulatory Build58 and GWAS4D59) appears to aid in regulatory variant prioritization, with probabilities for functional variants increasing substantially when using GWAS4D cell-dependent analyses with brain or monocytes”
From Genetic meta-analysis of diagnosed Alzheimer’s disease identifies new risk loci and implicates Aβ, tau, immunity and lipid processing (2019) · cites this paper as [58]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Fast and accurate short read alignment with Burrows-Wheeler transform
Li, H., & Durbin, R. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp324 · Cited by 58,607
BEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
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-citationJenuwein, T., & Allis, C. D. (2001) · Science · doi:10.1126/science.1063127 · Cited by 9,756
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
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
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y., & Greenleaf, W. J. (2013) · Nature Methods · doi:10.1038/nmeth.2688 · Cited by 6,422
Jaenisch, R., & Bird, A. (2003) · Nature Genetics · doi:10.1038/ng1089 · Cited by 6,325
Chen, X., Xiu, M., Xing, J., Yu, S., Min, D., & Guo, F. (2017) · Cellular Physiology and Biochemistry · doi:10.1159/000479439 · Cited by 5,760
Human DNA methylomes at base resolution show widespread epigenomic differences
Lister, R., Pelizzola, M., Dowen, R. H., Hawkins, R. D., Hon, G., Tonti-Filippini, J., Nery, J. R., Lee, L., Ye, Z., Ngo, Q.-M., et al. (2009) · Nature · doi:10.1038/nature08514 · Cited by 4,673
Cited by
Sorted by citations
Items 101–200 of 450
Extreme purifying selection against point mutations in the human genome
Dukler, N., Mughal, M. R., Ramani, R., Huang, Y.-F., & Siepel, A. C. (2022) · Nature Communications · doi:10.1038/s41467-022-31872-6 · Cited by 49
Williams, J. D., Houserova, D., Johnson, B. R., Dyniewski, B., Berroyer, A., French, H., Barchie, A. A., Bilbrey, D. D., DeMeis, J. D., Ghee, K. R., et al. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa357 · Cited by 45
Lesurf, R., Said, A., Akinrinade, O., Breckpot, J., Delfosse, K., Liu, T., Yao, R., Persad, G., McKenna, F., Noche, R. R., et al. (2022) · npj Genomic Medicine · doi:10.1038/s41525-022-00288-y · Cited by 49
Ogden, A., Rida, P. C. G., & Aneja, R. (2017) · Scientific Reports · doi:10.1038/s41598-017-00363-w · Cited by 47
Sex-specific associations with DNA methylation in lung tissue demonstrate smoking interactions
Koo, H., Morrow, J. D., Kachroo, P., Tantisira, K. G., Weiss, S. T., Hersh, C. P., Silverman, E. K., & DeMeo, D. L. (2020) · Epigenetics · doi:10.1080/15592294.2020.1819662 · Cited by 47
Cremer, M., Schmid, V. J., Kraus, F., Markaki, Y., Hellmann, I., Maiser, A., Leonhardt, H., John, S., Stamatoyannopoulos, J. A., & Cremer, T. (2017) · Epigenetics & Chromatin · doi:10.1186/s13072-017-0146-0 · Cited by 45
Mortlock, S., Restuadi, R., Levien, R., Girling, J. E., Holdsworth‐Carson, S. J., Healey, M., Zhu, Z., Qi, T., Wu, Y., Lukowski, S. W., et al. (2019) · Clinical Epigenetics · doi:10.1186/s13148-019-0648-7 · Cited by 42
Højfeldt, S. G., Wolthers, B. O., Tulstrup, M., Abrahamsson, J., Gupta, R., Harila‐Saari, A. H., Heyman, M. M., Henriksen, L. T., Jónsson, Ó. G., Lähteenmäki, P. M., et al. (2018) · British Journal of Haematology · doi:10.1111/bjh.15660 · Cited by 43
Unusual sequence characteristics of human chromosome 19 are conserved across 11 nonhuman primates
Harris, R. A., Raveendran, M., Worley, K. C., & Rogers, J. (2020) · BMC Evolutionary Biology · doi:10.1186/s12862-020-1595-9 · Cited by 40
Progress, Challenges, and Surprises in Annotating the Human Genome
Zerbino, D. R., Frankish, A., & Flicek, P. (2020) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-121119-083418 · Cited by 45
Self-citationPonomarenko, M. P., Рассказов, Д. А., Arkova, O. V., Пономаренко, П. М., Suslov, V. V., Savinkova, L. K., & Kolchanov, N. A. (2015) · BioMed Research International · doi:10.1155/2015/359835 · Cited by 44
Surapaneni, A., Schlosser, P., Zhou, L., Liu, C. S., Chatterjee, N., Arking, D. E., Dutta, D., Coresh, J., Rhee, E. P., & Grams, M. E. (2022) · Kidney International · doi:10.1016/j.kint.2022.07.005 · Cited by 44
Complementary evolution of coding and noncoding sequence underlies mammalian hairlessness
Kowalczyk, A. M., Chikina, M. D., & Clark, N. L. (2022) · eLife · doi:10.7554/elife.76911 · Cited by 39
Segway 2.0: Gaussian mixture models and minibatch training
Chan, R. C. W., Libbrecht, M. W., Roberts, E. G., Bilmes, J. A., Noble, W. S., & Hoffman, M. M. (2017) · Bioinformatics · doi:10.1093/bioinformatics/btx603 · Cited by 40
Epigenomic Convergence of Neural-Immune Risk Factors in Neurodevelopmental Disorder Cortex
Ciernia, A. V., Laufer, B. I., Hwang, H., Dunaway, K. W., Mordaunt, C. E., Coulson, R. L., Yasui, D. H., & LaSalle, J. M. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz115 · Cited by 39
Culture-Associated DNA Methylation Changes Impact on Cellular Function of Human Intestinal Organoids
Edgar, R. D., Perrone, F., Foster, A. R., Payne, F., Lewis, S., Nayak, K. M., Kraiczy, J., Cenier, A., Torrente, F., Salvestrini, C., et al. (2022) · Cellular and Molecular Gastroenterology and Hepatology · doi:10.1016/j.jcmgh.2022.08.008 · Cited by 40
Self-citationNuclear compartmentalization, dynamics, and function of regulatory DNA sequences
Cremer, M., & Cremer, T. J. (2018) · Genes Chromosomes and Cancer · doi:10.1002/gcc.22714 · Cited by 40
Zhang, H., Xu, Q., Jiang, Z., Sun, R., Wang, Q., Liu, S., Luan, X., Campisi, J., Kirkland, J. L., Zhang, W., et al. (2025) · Advanced Science · doi:10.1002/advs.202412950 · Cited by 46
An Xist-activating antisense RNA required for X-chromosome inactivation
Sarkar, M. K., Gayen, S., Kumar, S., Maclary, E. T., Buttigieg, E., Hinten, M., Kumari, A., Harris, C. E., Sado, T., & Kalantry, S. (2015) · Nature Communications · doi:10.1038/ncomms9564 · Cited by 37
ChromNet: Learning the human chromatin network from all ENCODE ChIP-seq data
Lundberg, S., Tu, W. B., Raught, B., Penn, L. Z., Hoffman, M. M., & Lee, S. (2016) · Genome biology · doi:10.1186/s13059-016-0925-0 · Cited by 36
Residential surrounding greenness and DNA methylation: An epigenome-wide association study
Xu, R., Li, S., Li, S., Wong, E. M., Southey, M. C., Hopper, J. L., Abramson, M. J., & Guo, Y. (2021) · Environment International · doi:10.1016/j.envint.2021.106556 · Cited by 38
Libbrecht, M. W., Chan, R. C. W., & Hoffman, M. M. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009423 · Cited by 36
Spinelli, R., Florese, P., Parrillo, L., Zatterale, F., Longo, M., D’Esposito, V., Desiderio, A., Nerstedt, A., Gustafson, B., Formisano, P., et al. (2022) · Aging Cell · doi:10.1111/acel.13557 · Cited by 35
Kado, S. Y., Chang, W. L. W., Nguyen, A., Wolny, M., Shepherd, D. M., & Vogel, C. F. A. (2016) · Archives of Toxicology · doi:10.1007/s00204-016-1896-3 · Cited by 36
Mosaic chromosomal alterations in blood across ancestries using whole-genome sequencing
Jakubek, Y. A., Zhou, Y., Stilp, A. M., Bacon, J., Wong, J., Özcan, Z., Arnett, D. K., Barnes, K. C., Bis, J. C., Boerwinkle, E., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01553-1 · Cited by 35
Genetic and neuroendocrine regulation of the postpartum brain
Gammie, S. C., Driessen, T. M., Zhao, C., Saul, M. C., & Eisinger, B. E. (2016) · Frontiers in Neuroendocrinology · doi:10.1016/j.yfrne.2016.05.002 · Cited by 36
Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia
Zhu, X., Zhou, B., Pattni, R., Gleason, K., Tan, C., Kalinowski, A., Sloan, S. A., Fiston-Lavier, A.-S., Mariani, J., Petrov, D. A., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-020-00767-4 · Cited by 35
Arkova, O. V., Ponomarenko, M. P., Рассказов, Д. А., Drachkova, I. A., Arshinova, T. V., Пономаренко, П. М., Savinkova, L. K., & Kolchanov, N. A. (2015) · BMC Genomics · doi:10.1186/1471-2164-16-s13-s5 · Cited by 34
Methylome and transcriptome profiling in Myasthenia Gravis monozygotic twins
Mamrut, S., Avidan, N., Truffault, F., Staun-Ram, E., Sharshar, T., Eymard, B., Frenkian, M., Piťha, J., Baets, M. H. D., Servais, L., et al. (2017) · Journal of Autoimmunity · doi:10.1016/j.jaut.2017.05.005 · Cited by 35
Gulko, B., & Siepel, A. C. (2018) · Nature Genetics · doi:10.1038/s41588-018-0300-z · Cited by 32
Functional Genomics of the Pediatric Obese Asthma Phenotype Reveal Enrichment of Rho-GTPase Pathways
Rastogi, D., Johnston, A. D., Nico, J., Loh, L. N., Jorge, Y., Suzuki, M., Macián, F., & Greally, J. M. (2020) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201906-1199oc · Cited by 34
Non‐coding variants in MYH11, FZD3, and SORCS3 are associated with dementia in women
Blue, E., Thornton, T. A., Kooperberg, C. L., Liu, S., Wactawski‐Wende, J., Manson, J. E., Kuller, L., Hayden, K. M., & Reiner, A. P. (2020) · Alzheimer s & Dementia · doi:10.1002/alz.12181 · Cited by 32
Smith, E., Somma, D., Kerrigan, D., McIntyre, Z., Cole, J., Liang, K. L., Kiely, P. A., Keeshan, K., & Carmody, R. J. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz873 · Cited by 32
Lagström, S., Løvestad, A. H., Umu, S. U., Ambur, O. H., Nygård, M., Rounge, T. B., & Christiansen, I. K. (2021) · Tumour Virus Research · doi:10.1016/j.tvr.2021.200221 · Cited by 33
Genomic architecture and functional effects of potential human inversion supergenes
Campoy, E., Puig, M., Yakymenko, I., Lerga-Jaso, J., & Cáceres, M. (2022) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2021.0209 · Cited by 32
Viloria, K., & Hill, N. J. (2016) · BioMolecular Concepts · doi:10.1515/bmc-2016-0004 · Cited by 34
Liang, J., Cade, B. E., He, K. Y., Wang, H., Lee, J., Sofer, T., Williams, S., Li, R., Chen, H., Gottlieb, D. J., et al. (2019) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2019.10.002 · Cited by 21
The molecular basis, genetic control and pleiotropic effects of local gene co-expression
Ribeiro, D. M., Rubinacci, S., Ramisch, A., Hofmeister, R. J., Dermitzakis, E. T., & Delaneau, O. (2021) · Nature Communications · doi:10.1038/s41467-021-25129-x · Cited by 31
Non‐coding regulatory elements: Potential roles in disease and the case of epilepsy
Pagni, S., Mills, J. D., Frankish, A., Mudge, J. M., & Sisodiya, S. M. (2021) · Neuropathology and Applied Neurobiology · doi:10.1111/nan.12775 · Cited by 33
Classification of non-coding variants with high pathogenic impact
Moyon, L., Berthelot, C., Louis, A., Nguyen, N. T. T., & Crollius, H. R. (2022) · PLoS Genetics · doi:10.1371/journal.pgen.1010191 · Cited by 34
Widespread cis-regulatory convergence between the extinct Tasmanian tiger and gray wolf
Feigin, C. Y., Newton, A. H., & Pask, A. J. (2019) · Genome Research · doi:10.1101/gr.244251.118 · Cited by 33
Beyond sequence: Structure-based machine learning
Durairaj, J., de Ridder, D., & van Dijk, A. D. J. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.12.039 · Cited by 32
Shipman, G. A., Padilla, R., Horth, C., Hu, B., Bareke, E., Vitorino, F. N. D. L., Gongora, J. M., Garcia, B. A., Lü, C., & Majewski, J. (2024) · Genome biology · doi:10.1186/s13059-024-03415-3 · Cited by 31
Dimitrakopoulos, C. M., Vrugt, B., Flury, R., Schraml, P., Knippschild, U., Wild, P. J., Hoerstrup, S. P., Henne‐Bruns, D., Wuerl, P., Graf, R., et al. (2019) · JAMA Surgery · doi:10.1001/jamasurg.2019.0484 · Cited by 30
Nguyen, Q. H., Tellam, R. L., Naval-Sánchez, M., Porto-Neto, L. R., Barendse, W., Reverter, A., Hayes, B. J., Kijas, J., & Dalrymple, B. P. (2018) · GigaScience · doi:10.1093/gigascience/gix136 · Cited by 29
Whole-genome sequencing of nine esophageal adenocarcinoma cell lines
Contino, G., Eldridge, M., Secrier, M., Bower, L., Elliott, R. F., Weaver, J. M. J., Lynch, A. G., Edwards, P. A., & Fitzgerald, R. C. (2016) · F1000Research · doi:10.12688/f1000research.7033.1 · Cited by 30
Early-life DNA methylation profiles are indicative of age-related transcriptome changes
Hadad, N., Masser, D. R., Blanco-Berdugo, L., Stanford, D. R., & Freeman, W. M. (2019) · Epigenetics & Chromatin · doi:10.1186/s13072-019-0306-5 · Cited by 29
Comprehensive longitudinal study of epigenetic mutations in aging
Wang, Y., Karlsson, R., Jylhävä, J., Hedman, Å. K., Almqvist, C., Karlsson, I., Pedersen, N. L., Almgren, M., & Hägg, S. (2019) · Clinical Epigenetics · doi:10.1186/s13148-019-0788-9 · Cited by 29
Chatterton, Z., Lamichhane, P., Rastegar, D. A., Fitzpatrick, L., Lebhar, H., Marquis, C. P., Halliday, G. M., & Kwok, J. B. (2023) · Cell & Bioscience · doi:10.1186/s13578-022-00938-9 · Cited by 27
Li, Y., Xu, J., Chen, C., Lu, Z., Wan, D., Li, D., Li, J. S., Sorg, A. J., Roberts, C. C., Mahajan, S., et al. (2024) · Genome Medicine · doi:10.1186/s13073-023-01280-6 · Cited by 28
Stable G-quadruplex enabling sequences are selected against by the context-dependent codon bias
Arachchilage, G. M., Arachchilage, M. H., Venkataraman, A., Piontkivska, H., & Basu, S. (2019) · Gene · doi:10.1016/j.gene.2019.02.006 · Cited by 27
Guo, X., Plank-Bazinet, J. L., Krivega, I. V., Dale, R., & Dean, A. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa736 · Cited by 30
Jones, M. R., Peng, P.-C., Coetzee, S. G., Tyrer, J. P., Reyes, A. L. P., Corona, R. I., Davis, B. D., Chen, S., Dezem, F. S., Seo, J.-H., et al. (2020) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2020.08.021 · Cited by 25
Integrative analysis of epigenetics data identifies gene-specific regulatory elements
Schmidt, F., Marx, A., Baumgarten, N., Hebel, M., Wegner, M., Kaulich, M., Leisegang, M. S., Brandes, R. P., Göke, J., Vreeken, J., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab798 · Cited by 25
Neikes, H. K., Kliza, K. W., Gräwe, C., Wester, R. A., Jansen, P. W. T. C., Lamers, L. A., Baltissen, M. P. A., van Heeringen, S. J., Logie, C., Teichmann, S. A., et al. (2023) · Nature Biotechnology · doi:10.1038/s41587-023-01715-w · Cited by 28
Mortensen, H. M., Chamberlin, J., Joubert, B. R., Angrish, M. M., Sipes, N. S., Lee, J. S., & Euling, S. Y. (2018) · Mammalian Genome · doi:10.1007/s00335-018-9738-7 · Cited by 30
The open targets post-GWAS analysis pipeline
Peat, G., Jones, W., Nuhn, M., Marugán, J. C., Newell, W. R., Dunham, I., & Zerbino, D. R. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa020 · Cited by 26
Self-citationPOU6f1 Mediates Neuropeptide-Dependent Plasticity in the Adult Brain
McClard, C. K., Kochukov, M. Y., Herman, I., Liu, Z., Eblimit, A., Moayedi, Y., Ortiz‐Guzman, J., Colchado, D., Pekarek, B. T., Panneerselvam, S., et al. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.1641-17.2017 · Cited by 28
Large-Scale Multi-Omics Studies Provide New Insights into Blood Pressure Regulation
Kamali, Z., Keaton, J. M., Javanmard, S. H., Program, M. V., Edwards, T. L., Snieder, H., & Vaez, A. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms23147557 · Cited by 24
Чадаева, И. В., Ponomarenko, M. P., Рассказов, Д. А., Sharypova, E. B., Kashina, E. V., Matveeva, M. Y., Arshinova, T. V., Пономаренко, П. М., Arkova, O. V., Bondar, N. P., et al. (2016) · BMC Genomics · doi:10.1186/s12864-016-3353-3 · Cited by 25
Bao, Y., Gabrielpillai, J., Dietrich, J., Zarbl, R., Strieth, S., Schröck, F., & Dietrich, D. (2021) · Clinical Epigenetics · doi:10.1186/s13148-021-01212-4 · Cited by 24
Functional Characterization of Genetic Variant Effects on Expression
Flynn, E. D., & Lappalainen, T. (2022) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-122120-010010 · Cited by 24
RegulationSpotter: annotation and interpretation of extratranscriptic DNA variants
Schwarz, J. M., Hombach, D., Köhler, S., Cooper, D. N., Schuelke, M., & Seelow, D. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz327 · Cited by 23
Koker, A. D., Raman, L., Paemel, R. V., der Linden, M. V., de Velde, S. V., van der Leest, P., Gaever, B. V., Zaka, A., Vermaelen, K., Demedts, I., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/663195 · Cited by 24
Auckland, K., Mittal, B., Cairns, B. J., Garg, N. K., Kumar, S., Mentzer, A. J., Kado, J. H., Perman, M. L., Steer, A. C., Hill, A. V. S., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-65855-8 · Cited by 24
Zhu, Y., Lee, H., White, S. M., Weimer, A. K. K., Monte, E., Horning, A. M., Nevins, S. A., Esplin, E. D., Paul, K., Krieger, G., et al. (2024) · Nature Cancer · doi:10.1038/s43018-024-00823-z · Cited by 24
Ponomarenko, M. P., Arkova, O. V., Рассказов, Д. А., Пономаренко, П. М., Savinkova, L. K., & Kolchanov, N. A. (2016) · Frontiers in Immunology · doi:10.3389/fimmu.2016.00130 · Cited by 24
Safety evaluation of conditionally immortalized cells for renal replacement therapy
Mihajlovic, M., Hariri, S., Westphal, K. G. C., Janssen, M. J., Oost, M. J., Bongiovanni, L., van den Heuvel, L. P., de Bruin, A., Hilbrands, L. B., & Masereeuw, R. (2019) · Oncotarget · doi:10.18632/oncotarget.27152 · Cited by 23
Rhee, E. P., Surapaneni, A., Zheng, Z., Zhou, L., Dutta, D., Arking, D. E., Zhang, J., Duong, T., Chatterjee, N., Luo, S., et al. (2022) · Kidney International · doi:10.1016/j.kint.2022.01.014 · Cited by 21
Computational Methods for Single-Cell DNA Methylome Analysis
Iqbal, W., & Zhou, W. (2022) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2022.05.007 · Cited by 24
TULIPs decorate the three-dimensional genome of PFA ependymoma
Johnston, M. J. G., Lee, J. J. Y., Hu, B., Nikolić, A., Hasheminasabgorji, E., Baguette, A., Paik, S., Chen, H., Kumar, S. A., Chen, C. C. L., et al. (2024) · Cell · doi:10.1016/j.cell.2024.06.023 · Cited by 22
Accurate prediction of cis -regulatory modules reveals a prevalent regulatory genome of humans
Ni, P., & Su, Z. (2021) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqab052 · Cited by 23
Kierczak, M., Rafati, N., Höglund, J., Gourlé, H., Lo Faro, V., Schmitz, D., Ek, W. E., Gyllensten, U., Enroth, S., Ekman, D., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30208-8 · Cited by 22
Laverrière, J., L’Hôte, D., Tabouy, L., Schang, A., Quérat, B., & Cohen-Tannoudji, J. (2016) · Molecular and Cellular Endocrinology · doi:10.1016/j.mce.2016.07.010 · Cited by 25
Fernandes, S. J., Morikawa, H., Ewing, E., Ruhrmann, S., Joshi, R. N., Lagani, V., Karathanasis, N., Khademi, M., Planell, N., Schmidt, A., et al. (2019) · Scientific Reports · doi:10.1038/s41598-019-48493-7 · Cited by 22
Human Stem Cell Resources Are an Inroad to Neandertal DNA Functions
Dannemann, M., He, Z., Heide, C., Vernot, B., Sidow, L., Kanton, S., Weigert, A., Treutlein, B., Pääbo, S., Kelso, J. F., et al. (2020) · Stem Cell Reports · doi:10.1016/j.stemcr.2020.05.018 · Cited by 22
Genome diversity and signatures of natural selection in mainland Southeast Asia
He, Y., Zhang, X., Peng, M., Li, Y.-C., Liu, K., Zhang, Y., Mao, L., Guo, Y., Ma, Y., Zhou, B., et al. (2025) · Nature · doi:10.1038/s41586-025-08998-w · Cited by 24
De novopattern discovery enables robust assessment of functional consequences of non-coding variants
Hai, Y., Chen, R., Wang, Q., Wei, Q., Ji, Y., Zheng, G., Zhong, X. Y., Cox, N. J., & Li, B. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty826 · Cited by 19
Liu, L., Zhang, L., Dao, F., Yang, Y., & Lin, H. (2020) · Molecular Therapy — Nucleic Acids · doi:10.1016/j.omtn.2020.11.011 · Cited by 21
Stackhouse, C. T., Anderson, J. C., Yue, Z., Nguyen, T. M., Eustace, N. J., Langford, C. P., Wang, J., Rowland, J. R., Xing, C., Mikhail, F. M., et al. (2022) · JCI Insight · doi:10.1172/jci.insight.148717 · Cited by 23
Bartas, M., Brázda, V., Karlický, V., Červeň, J., & Pečínka, P. (2018) · Biochimie · doi:10.1016/j.biochi.2018.05.002 · Cited by 21
Ma, X., & Xu, S. (2022) · iScience · doi:10.1016/j.isci.2022.105614 · Cited by 22
Pan, Y., Wen, J., Ning, Z., Yuan, Y., Liu, X., Yang, Y., Guan, Y., Lü, Y., Mamatyusupu, D., & Xu, S. (2023) · Molecular Biology and Evolution · doi:10.1093/molbev/msad054 · Cited by 20
Major Genetic Risk Factors for Dupuytren's Disease Are Inherited From Neandertals
Ågren, R., Patil, S. B., Zhou, X., FinnGen., Palotie, A. V., Daly, M. J., Riley-Gills, B., Jacob, H. J., Paul, D. S., Matakidou, A., et al. (2023) · Molecular Biology and Evolution · doi:10.1093/molbev/msad130 · Cited by 21
Regulation of PPARGC1A gene expression in trained and untrained human skeletal muscle
Popov, D. V., Lysenko, E. A., Makhnovskii, P. A., Kurochkina, N. S., & Виноградова, О. Л. (2017) · Physiological Reports · doi:10.14814/phy2.13543 · Cited by 20
Jian, X., Sofer, T., Tarraf, W., Bressler, J., Faul, J. D., Zhao, W., Ratliff, S. M., Lamar, M., Launer, L. J., Laurie, C. C., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-00930-2 · Cited by 22
Local patterns of genetic sharing between neuropsychiatric and insulin resistance-related conditions
Fanelli, G., Franke, B., Fabbri, C., Werme, J., Erdogan, I., Witte, W. D., Poelmans, G., Ruisch, I. H., Reus, L. M., van Gils, V., et al. (2025) · Translational Psychiatry · doi:10.1038/s41398-025-03349-9 · Cited by 24
Ponomarenko, P. M., Рассказов, Д. А., Suslov, V. V., Sharypova, E. B., Savinkova, L. K., Podkolodnaya, O. A., Podkolodnyy, N. L., Tverdokhleb, N. N., Витальевна, Ч. И., Ponomarenko, M. P., et al. (2016) · BioMed Research International · doi:10.1155/2016/8642703 · Cited by 19
Витальевна, Ч. И., Ponomarenko, P. M., Рассказов, Д. А., Sharypova, E. B., Kashina, E. V., Zhechev, D. A., Drachkova, I. A., Arkova, O. V., Savinkova, L. K., Ponomarenko, M. P., et al. (2018) · BMC Genomics · doi:10.1186/s12864-018-4478-3 · Cited by 19
Smits, J. J., de Bruijn, S. E., Lanting, C., Oostrik, J., O’Gorman, L., Mantere, T., van Dooren, M. F., Kant, S. G., de Gier, H. H. W., Hoefsloot, E. H., et al. (2021) · Human Genetics · doi:10.1007/s00439-021-02336-6 · Cited by 20
Expression of immunoglobulin constant domain genes in neurons of the mouse central nervous system
Scheurer, L., Gupta, R. R. D., Saebisch, A., Grampp, T., Benke, D., Zeilhofer, H. U., & Wildner, H. (2021) · Life Science Alliance · doi:10.26508/lsa.202101154 · Cited by 17
Recent advances in the genomic resources for sheep
Woolley, S. A., Salavati, M., & Clark, E. L. (2023) · Mammalian Genome · doi:10.1007/s00335-023-10018-z · Cited by 21
Nakayama, N., Sakashita, G., Nagata, T., Kobayashi, N., Yoshida, H., Park, S.-Y., Nariai, Y., Kato, H., Obayashi, E., Nakayama, K., et al. (2020) · Biomedicines · doi:10.3390/biomedicines8120608 · Cited by 15
An Amish founder population reveals rare-population genetic determinants of the human lipidome
Montasser, M. E., Aslibekyan, S. W., Srinivasasainagendra, V., Tiwari, H. K., Patki, A., Bagheri, M., Kind, T., Barupal, D. K., Fan, S., Perry, J. A., et al. (2022) · Communications Biology · doi:10.1038/s42003-022-03291-2 · Cited by 18
de Vries, P. S., Conomos, M. P., Singh, K., Nicholson, C., Jain, D., Hasbani, N. R., Jiang, W., Lee, S., Cardenas, C. L. L., Lutz, S. M., et al. (2023) · Nature Cardiovascular Research · doi:10.1038/s44161-023-00375-y · Cited by 17
Genetic coupling of enhancer activity and connectivity in gene expression control
Ray-Jones, H. F., Sung, C. K., Chan, L. T., Haglund, A., Artemov, P., Rosa, M. D., Ruje, L., Burden, F., Kreuzhuber, R., Litovskikh, A., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-55900-3 · Cited by 17
Complement receptor 1 (CR1, CD35) association with susceptibility to leprosy
Kretzschmar, G. C., Oliveira, L. C., Nisihara, R., Velavan, T. P., Stinghen, S. T., Stahlke, E. R. S., Petzl‐Erler, M. L., Messias-Reason, I., & Boldt, A. B. W. (2018) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0006705 · Cited by 17
MutSpot: detection of non-coding mutation hotspots in cancer genomes
Guo, Y. A., Chang, M. M., & Skanderup, A. J. (2020) · npj Genomic Medicine · doi:10.1038/s41525-020-0133-4 · Cited by 15
Wang, Y., Nudel, R., Benros, M. E., Skogstrand, K., Fishilevich, S., iPSYCH-BROAD, Lancet, D., Sun, J., Hougaard, D. M., Andreassen, O. A., et al. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1009163 · Cited by 16
MutationalPatterns: The one stop shop for the analysis of mutational processesPreprint
Manders, F., Brandsma, A. M., de Kanter, J. K., Verheul, M., Oka, R., van Roosmalen, M. J., der Roest, B. R. V., van Hoeck, A., Cuppen, E. P. J. G., & van Boxtel, R. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.01.466730 · Cited by 17
Metadata
- Authors
- Zerbino, D. R., Wilder, S. P., Johnson, N., Juettemann, T., & Flicek, P. R.
- Affiliations
- European Bioinformatics Institute (GB)
- Corresponding author
- Zerbino, Daniel R
- Flicek, Paul R
- Venue
- Genome Biology
- Published
- 2015-03-24
- Volume
- 16
- Issue
- 1
- Pages
- 56-56
- ISSN
- 1465-6906 (ISSN-L)
- PMC
- PMC4407537
- OpenAlex
- W2102659607
- Cited by
- 429
- References
- 53
- Citations by year
- 2026: 8 · 2025: 24 · 2024: 40 · 2023: 45 · 2022: 61 · 2021: 47 · 2020: 52 · 2019: 51 · 2018: 35 · 2017: 23 · 2016: 34 · 2015: 8
- FWCI
- 14.47
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Wellcome Trust (FP7/2007–2013, 095908, WT095908, 223210)
- European Molecular Biology Laboratory
- European Commission (226073, 282510, 2007–2013, FP7 2007-2013, FP7/2007, 223210)
- Directorate for Biological Sciences
- Biotechnology and Biological Sciences Research Council (BB/I025360/2)
- National Human Genome Research Institute (U01HG004695)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Keywords
- regulatory elements, epigenetic modifications, transcription factor binding, human genome annotation, non-coding variants, variant interpretation
- MeSH terms
- Humans, Software, Transcription Factors, User-Computer Interface, Computational Biology, Internet, Genomics, Databases, Genetic, Epigenesis, Genetic
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