The DOI matches its Crossref record; 47 of the 48 references it cites were found in a registry or an index.
Genome-Wide Quantitative Enhancer Activity Maps Identified by STARR-seq
Abstract
Genomic enhancers are important regulators of gene expression, but their identification is a challenge, and methods depend on indirect measures of activity. We developed a method termed STARR-seq to directly and quantitatively assess enhancer activity for millions of candidates from arbitrary sources of DNA, which enables screens across entire genomes. When applied to the Drosophila genome, STARR-seq identifies thousands of cell type-specific enhancers across a broad continuum of strengths, links differential gene expression to differences in enhancer activity, and creates a genome-wide quantitative enhancer map. This map reveals the highly complex regulation of transcription, with several independent enhancers for both developmental regulators and ubiquitously expressed genes. STARR-seq can be used to identify and quantify enhancer activity in other eukaryotes, including humans.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
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
“In contrast with MPRAs relying on re-synthesis of candidate sequences, genome-wide ‘shotgun MPRAs’108,174,183,188 nicely avoid a priori assumptions about which sequences to test.”
From Towards a comprehensive catalogue of validated and target-linked human enhancers (2020) · cites this paper as [174]
In the citing paper
“Finally, evidence from multiple sources including reporter assays [169, 175, 239, 240], CRISPR [240–242], chromatin mapping [243, 244] and population genetics analysis [207, 245] suggests that certain promoters, termed ‘epromoters’, can also function as enhancers (reviewed in [246]).”
From Transcriptional enhancers and their communication with gene promoters (2021) · cites this paper as [169]
Citations
Cites
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
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
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
The Human Genome Browser at UCSC
Kent, W. J., Sugnet, C. W., Furey, T. S., Roskin, K. M., Pringle, T. H., Zahler, A. M., & Haussler, A. D. (2002) · Genome Research · doi:10.1101/gr.229102 · Cited by 10,400
Targeted gene expression as a means of altering cell fates and generating dominant phenotypes
Brand, A. H., & Perrimon, N. (1993) · Development · doi:10.1242/dev.118.2.401 · Cited by 9,510
Tandem repeats finder: a program to analyze DNA sequences
Benson, G. (1999) · Nucleic Acids Research · doi:10.1093/nar/27.2.573 · Cited by 9,374
The Genome Sequence of Drosophila melanogaster
Adams, M. D., Celniker, S., Holt, R. A., Evans, C. A., Gocayne, J. D., Amanatides, P. G., Scherer, S. E., Li, P. W., Hoskins, R. A., Galle, R. F., et al. (2000) · Science · doi:10.1126/science.287.5461.2185 · Cited by 5,902
Histone H3K27ac separates active from poised enhancers and predicts developmental state
Creyghton, M. P., Cheng, A. W., Welstead, G. G., Kooistra, T., Carey, B. W., Steine, E. J., Hanna, J., Lodato, M. A., Frampton, G. M., Sharp, P. A., et al. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1016071107 · Cited by 4,302
miRBase: integrating microRNA annotation and deep-sequencing data
Kozomara, A., & Griffiths-Jones, S. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1027 · Cited by 3,634
Cited by
Sorted by citations
Items 601–700 of 1,000
Deciphering the Gene Regulatory Landscape Encoded in DNA Biophysical Features
Pataskar, A., Vanderlinden, W., Emmerig, J., Singh, A. P., Lipfert, J., & Tiwari, V. K. (2019) · iScience · doi:10.1016/j.isci.2019.10.055 · Cited by 9
How to study enhancers in non-traditional insect models
Tomoyasu, Y., & Halfon, M. S. (2020) · Journal of Experimental Biology · doi:10.1242/jeb.212241 · Cited by 9
Baxter, J. S., Johnson, N., Tomczyk, K., Gillespie, A., Maguire, S. L., Brough, R., Fachal, L., Michailidou, K., Bolla, M. K., Wang, Q., et al. (2021) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2021.05.013 · Cited by 9
Multiplexed functional genomic assays to decipher the noncoding genome
Cooper, Y. A., Guo, Q., & Geschwind, D. H. (2022) · Human Molecular Genetics · doi:10.1093/hmg/ddac194 · Cited by 10
DNA methylation-environment interactions in the human genome
Johnston, R. A., Aracena, K. A., Barreiro, L. B., Lea, A. J., & Tung, J. (2023) · eLife · doi:10.7554/elife.89371 · Cited by 8
Cico, A., Andrieu‐Soler, C., & Soler, É. (2016) · FEBS Letters · doi:10.1002/1873-3468.12424 · Cited by 11
Direct visualization of transcriptional activation by physical enhancer–promoter proximityPreprint
Chen, H., Fujioka, M., Jaynes, J. B., & Gregor, T. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/099523 · Cited by 11
Monsen, Ø., Grønvold, L., Datsomor, A. K., Harvey, T. N., Kijas, J., Suh, A., Hvidsten, T. R., & Sandve, S. R. (2025) · Genome Research · doi:10.1101/gr.278931.124 · Cited by 8
Esearch3D: propagating gene expression in chromatin networks to illuminate active enhancers
Heer, M., Giudice, L., Mengoni, C., Giugno, R., & Rico, D. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad229 · Cited by 8
Guzman, C., Duttke, S. H. C., Zhu, Y., Saldanha, C. D. A., Downes, N. L., Benner, C. W., & Heinz, S. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad562 · Cited by 7
Identification, Design, and Application of Noncoding Cis-Regulatory Elements
Xu, L., & Liu, Y. (2024) · Biomolecules · doi:10.3390/biom14080945 · Cited by 9
Translation of genome-wide association study: from genomic signals to biological insights
Bruner, W. S., & Grant, S. F. A. (2024) · Frontiers in Genetics · doi:10.3389/fgene.2024.1375481 · Cited by 10
Towards functional maps of non-coding variants in cancer
Wang, Y., & Hon, G. C. (2024) · Frontiers in Genome Editing · doi:10.3389/fgeed.2024.1481443 · Cited by 8
Jones, B. M., Webb, A. E., Geib, S. M., Sim, S. B., Schweizer, R. M., Branstetter, M. G., Evans, J. D., & Kocher, S. D. (2024) · Molecular Biology and Evolution · doi:10.1093/molbev/msae229 · Cited by 8
Technical and biological sources of noise confound multiplexed enhancer AAV screening
Hunker, A. C., Mich, J. K., Taskin, N., Torkelson, A., Cardenas, T., Lalanne, J., Mahoney, J. T., Bertagnolli, D., Chakka, A. B., Chakrabarty, R., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-72147-8 · Cited by 8
Ahsen, M. E. (2025) · Mathematics · doi:10.3390/math13030420 · Cited by 10
Chignon, A., & Lettre, G. (2025) · Atherosclerosis · doi:10.1016/j.atherosclerosis.2024.118621 · Cited by 9
Chen, W., Wang, Z., Wang, Y., Lin, J., Chen, S., Chen, H., Ma, X., Zou, X., Li, X., Qin, Y., et al. (2025) · Advanced Science · doi:10.1002/advs.202411974 · Cited by 8
DNA G-quadruplex structures act as functional elements in α- and β-globin enhancers
Doyle, C., Herka, K., Flynn, S. M., Melidis, L., Dhir, S., Schoenfelder, S., Tannahill, D., & Balasubramanian, S. (2025) · Genome biology · doi:10.1186/s13059-025-03627-1 · Cited by 10
Lineage-specific regulatory evolution: insights from massively parallel reporter assays
Easterlin, R., & Ahituv, N. (2025) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2025.102372 · Cited by 6
Identification and application of bioparts for plant synthetic biology
Koo, H., Jung, M., Lee, S., Go, S., & Kim, Y. (2025) · Molecules and Cells · doi:10.1016/j.mocell.2025.100273 · Cited by 8
Zhang, Y., Dai, L., Dou, Y., Li, X., Lu, C. F., & Wu, H. (2025) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2025.3620986 · Cited by 8
Super-enhancer landscape rewiring in cancer: The epigenetic control at distal sites
Giorgio, E. D., Benetti, R., Kerschbamer, E., Xodo, L. E., & Brancolini, C. (2023) · International review of cytology · doi:10.1016/bs.ircmb.2023.03.013 · Cited by 9
Chen, X., Duan, Y.-Y., Jia, Y., Dong, Q.-H., Shi, W., Zhang, Y., Dong, S., Li, M., Liu, Z., Chen, F., et al. (2024) · Cell Genomics · doi:10.1016/j.xgen.2024.100501 · Cited by 8
From sequence to consequence: Deciphering the complex cis-regulatory landscape
Dsilva, G. J., & Galande, S. (2024) · Journal of Biosciences · doi:10.1007/s12038-024-00431-0 · Cited by 9
Fan, S., Ma, L., Song, C., Xu, H., Zhong, B., & Lin, Y. (2024) · Cell Systems · doi:10.1016/j.cels.2024.08.007 · Cited by 8
Transcription-controlling regulatory elements of the eukaryotic genome
Razin, S. V., Gavrilov, A. A., & Ulianov, S. V. (2015) · Molecular Biology · doi:10.1134/s0026893315020119 · Cited by 8
Deciphering enhancer sequence using thermodynamics-based models and convolutional neural networks
Dibaeinia, P., & Sinha, S. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkab765 · Cited by 8
Molecular and experimental tools to design synthetic enhancers
Vaknin, I., & Amit, R. (2022) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2022.102728 · Cited by 8
STARR-seq for high-throughput identification of plant enhancers
Zhang, L., Yung, W., & Huang, M. (2022) · Trends in Plant Science · doi:10.1016/j.tplants.2022.08.008 · Cited by 8
Schofield, J. A., & Hahn, S. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112387 · Cited by 9
Yang, X. H., Wang, B., & Cunningham, J. M. (2015) · BMC Medical Genomics · doi:10.1186/1755-8794-8-s2-s6 · Cited by 8
Russo, M., Natoli, G., & Ghisletti, S. (2017) · Transcription · doi:10.1080/21541264.2017.1378158 · Cited by 8
Anaemia, macrocytosis, vitamin B12 and folate levels in elderly Zimbabweans.
Allain, T. J., Gomo, Z. A. R., Wilson, A. O., Ndemera, B., Adamchak, D. J., & Matenga, J. A. (1997) · PubMed · Cited by 8
Simple Expression Domains Are Regulated by Discrete CRMs During Drosophila Oogenesis
Revaitis, N. T., Marmion, R. A., Farhat, M., Ekiz, V., Wang, W., & Yakoby, N. (2017) · G3 Genes Genomes Genetics · doi:10.1534/g3.117.043810 · Cited by 8
Sequence-based correction of barcode bias in massively parallel reporter assaysPreprint
Lee, D., Kapoor, A., Lee, C., Mudgett, M., Beer, M., & Chakravarti, A. (2021) · Genome Research · doi:10.1101/gr.268599.120 · Cited by 8
Massively parallel approaches for characterizing noncoding functional variation in human evolution
Rong, S., Root, E., & Reilly, S. K. (2024) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2024.102256 · Cited by 9
Integrating Arabidopsis and crop species gene discovery for crop improvement
Bevan, M. W., Messerer, M., Gundlach, H., Kamal, N. M., Hall, A. J. W., Spannagl, M., & Mayer, K. (2025) · The Plant Cell · doi:10.1093/plcell/koaf087 · Cited by 6
Human Synthetic Biology and Programmable Gene Regulation Control
Thurm, A. R., Carattini, G. L. J., & Bintu, L. (2025) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-120423-013542 · Cited by 7
Large-scale discovery of potent, compact and erythroid specific enhancers for gene therapy vectors
Psatha, N., Sova, P., Georgolopoulos, G., Paschoudi, K., Iwata, M., Bloom, J. E., Ulyanova, T., Wang, H., Kirtsou, A., Vasiloudis, N.-I., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-59235-x · Cited by 9
Robust regulatory interplay of enhancers, facilitators, and promoters in a native chromatin context
Zhou, Z., Cheng, Y., Lieberth, J., Zhang, J., Jin, Y., Li, A., Yu, H., Ozer, A., & Lis, J. T. (2026) · Cell · doi:10.1016/j.cell.2026.06.033 · Cited by 11
Dong, D., Zi-Sheng, W. A. N. G., Liu, M., Zhang, Q., Xu, W., Yu, W., Zhu, J., Yang, X., Zhang, Q., Zhu, Y., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-64005-w · Cited by 7
3D‐Epigenomic Regulation of Gene Transcription in Hepatocellular Carcinoma
Feng, Y., Wang, P., Cai, L., Zhan, M., He, F., Wang, J., Li, Y., Gega, E., Zhang, W., Zhao, W., et al. (2022) · Advanced Genetics · doi:10.1002/ggn2.202100010 · Cited by 7
Translating non-coding genetic associations into a better understanding of immune-mediated disease
Stankey, C. T., & Lee, J. C. (2023) · Disease Models & Mechanisms · doi:10.1242/dmm.049790 · Cited by 9
MAE-seq refines regulatory elements across the genome
Zhu, X., Huang, Q., Huang, L., Luo, J., Li, Q., Kong, D., Deng, B., Gu, Y., Wang, X., Li, C., et al. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad1129 · Cited by 8
Wang, C., Chen, C., Lei, B., Qin, S., Zhang, Y., Li, K., Zhang, S., & Liu, Y. (2024) · Genetics Selection Evolution · doi:10.1186/s12711-024-00897-4 · Cited by 8
Murray, J. I. (2018) · Wiley Interdisciplinary Reviews Developmental Biology · doi:10.1002/wdev.314 · Cited by 8
Heart Enhancers: Development and Disease Control at a Distance
Yuan, X., Scott, I. C., & Wilson, M. D. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.642975 · Cited by 7
Gui, Y., Grzyb, K., Thomas, M. H., Ohnmacht, J., Garcia, P., Buttini, M., Skupin, A., Sauter, T., & Sinkkonen, L. (2021) · Epigenetics & Chromatin · doi:10.1186/s13072-021-00418-3 · Cited by 7
Underlying causes for prevalent false positives and false negatives in STARR-seq data
Ni, P., Wu, S., & Su, Z. (2023) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqad085 · Cited by 8
SilenceREIN: seeking silencers on anchors of chromatin loops by deep graph neural networks
Pan, J.-H., & Du, P.-F. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad494 · Cited by 7
Uvarova, A. N., Ткаченко, Е. А., Stasevich, E. M., Zheremyan, E. A., Korneev, K. V., & Kuprash, D. V. (2024) · Biochemistry (Moscow) · doi:10.1134/s0006297924060026 · Cited by 7
Chromatin Properties of Regulatory DNA Probed by Manipulation of Transcription Factors
Sharov, A. A., Nishiyama, A., Qian, Y., Dudekula, D. B., Longo, D. L., Schlessinger, D., & Ko, M. S. H. (2014) · Journal of Computational Biology · doi:10.1089/cmb.2013.0126 · Cited by 7
On the cause and mechanism of phenoptosis
Walker, R. F. (2017) · Biochemistry (Moscow) · doi:10.1134/s0006297917120069 · Cited by 7
CAMIO: a transgenic CRISPR pipeline to create diverse targeted genome deletions in Drosophila
Chen, H.-M., García‐Marqués, J., Sugino, K., Wei, D., Miyares, R. L., & Lee, T. (2020) · Nucleic Acids Research · doi:10.1093/nar/gkaa177 · Cited by 8
Arora, A., Gutierrez, R. C., Eletto, D., Becker, R., Brown, M. R., Moor, A. E., Russ, H. A., & Taliaferro, J. M. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.20.465152 · Cited by 7
Kribelbauer, J. F., Gardeux, V., Llimos, G., Faltejsková, K., Russeil, J., Grenningloh, N., Levassor, L., Steiner, C., Vondrášek, J., & Deplancke, B. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.12.08.627402 · Cited by 6
Crosstalk between paralogs and isoforms influences p63-dependent regulatory element activity
Baniulyte, G., McCann, A. A., Woodstock, D. L., & Sammons, M. A. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1143 · Cited by 6
Wan, J., van Ouwerkerk, A. F., Mouren, J.-C., Heredia, C., Pradel, L. C., Ballester, B., Andrau, J., & Spicuglia, S. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae1270 · Cited by 7
High‐throughput quantitative assessment of ABA‐responsive elements at single‐nucleotide resolution
Sun, F., Deng, Y., Zhao, W., Xiong, Y., Zhao, L., & Zhang, L. (2025) · Quantitative Biology · doi:10.1002/qub2.87 · Cited by 6
Cuomo, M., Costabile, D., Monica, R. D., Buonaiuto, M., Trio, F., Riso, G. D., Visconti, R., & Chiariotti, L. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf274 · Cited by 7
Zhang, J., Leung, A. K.-Y., Zhu, Y., Yao, L., Willis, A., Pan, X., Ozer, A., Zhou, Z., Siklenka, K., Barrera, A., et al. (2025) · Genome biology · doi:10.1186/s13059-025-03828-8 · Cited by 7
Quantitative analysis of cis-regulatory elements in transcription with KAS-ATAC-seq
Lyu, R., Gao, Y., Wu, T., Ye, C., Wang, P., & He, C. (2024) · Nature Communications · doi:10.1038/s41467-024-50680-8 · Cited by 7
How our brains are built: emerging approaches to understand human-specific features
Moss, N. D., Lollis, D., & Silver, D. L. (2024) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2024.102278 · Cited by 7
Machine learning and deep learning for the advancement of epigenomics
Machnicka, M. A., & Wilczyński, B. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-817964-2.00009-5 · Cited by 6
Functional genomics and epigenomics of atrial fibrillation
Victorino, J., Álvarez, A., & Manzanares, M. (2021) · Journal of Molecular and Cellular Cardiology · doi:10.1016/j.yjmcc.2021.04.003 · Cited by 6
Cis-regulatory atlas of primary human CD4+ T cells
Stefan, K., & Barski, A. (2023) · BMC Genomics · doi:10.1186/s12864-023-09288-3 · Cited by 6
Toward Identification of Functional Sequences and Variants in Noncoding DNA
Monti, R., & Ohler, U. (2023) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-122120-110102 · Cited by 6
Cis-regulatory variation: significance in biomedicine and evolution
Friedensohn, S., & Sawarkar, R. (2014) · Cell and Tissue Research · doi:10.1007/s00441-014-1855-3 · Cited by 6
Genome-wide identification of hypoxia-induced enhancer regions
Kamps‐Hughes, N., Preston, J. L., Randel, M. A., & Johnson, E. A. (2015) · PeerJ · doi:10.7717/peerj.1527 · Cited by 6
Studying a novel ecdysone-dependent enhancer
Nikolenko, J. V., Краснов, А. Н., Mazina, M. Y., Georgieva, S. G., & Vorobyeva, N. E. (2017) · Doklady Biochemistry and Biophysics · doi:10.1134/s160767291703022x · Cited by 6
Wang, H. V., & Chekanova, J. A. (2019) · RNA · doi:10.1261/rna.071209.119 · Cited by 6
Penzar, D., Zinkevich, A. O., Vorontsov, I. E., Sitnik, V. V., Favorov, A. V., Makeev, V. J., & Kulakovskiy, I. V. (2019) · Frontiers in Genetics · doi:10.3389/fgene.2019.01078 · Cited by 6
Mod(mdg4) variants repress telomeric retrotransposon HeT-A by blocking subtelomeric enhancers
Takeuchi, C., Yokoshi, M., Kondo, S., Shibuya, A., Saito, K., Fukaya, T., Siomi, H., & Iwasaki, Y. W. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac1034 · Cited by 6
Dionne, N., Dib, S., Finsen, B. R., Denarier, É., Kuhlmann, T., Drouin, R., Kokoeva, M. V., Hudson, T. J., Siminovitch, K. A., Friedman, H. C., et al. (2015) · Glia · doi:10.1002/glia.22923 · Cited by 5
Muerdter, F., Boryń, Ł. M., Woodfin, A. R., Neumayr, C., Rath, M., Zabidi, M. M. A., Pagani, M., Haberle, V., Kazmar, T., Catarino, R. R., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/164590 · Cited by 6
Self-citationAtrial Fibrillation Is a Complex Trait
Shoemaker, M. B., & Roden, D. M. (2020) · Circulation Research · doi:10.1161/circresaha.120.317112 · Cited by 5
Genome-wide strand asymmetry in massively parallel reporter activity favors genic strandsPreprint
Roberts, B. S., Partridge, E. C., Moyers, B. A., Agarwal, V., Newberry, K. M., Martin, B., Shendure, J., Myers, R., & Cooper, G. M. (2021) · Genome Research · doi:10.1101/gr.270751.120 · Cited by 6
Delandre, C., McMullen, J. P. D., Paulsen, J., Collas, P., & Marshall, O. J. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.10.30.514435 · Cited by 6
Chromatin states at homeoprotein loci distinguish axolotl limb segments prior to regenerationPreprint
Kawaguchi, A., Wang, J., Knapp, D., Murawala, P., Nowoshilow, S., Masselink, W., Taniguchi‐Sugiura, Y., Fei, J., & Tanaka, E. M. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.14.516253 · Cited by 6
CRISPRi with barcoded expression reporters dissects regulatory networks in human cellsPreprint
Kim, J., Muller, R. Y., Bondra, E. R., & Ingolia, N. T. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.09.06.611573 · Cited by 6
Huang, Y., Verstegen, M. J. A. M., Tjalsma, S. J. D., Krijger, P. H. L., Gupta, K., Park, M., Boettiger, A. N., & de Laat, W. L. (2025) · Genes & Development · doi:10.1101/gad.352235.124 · Cited by 7
Defining the fine structure of promoter activity on a genome-wide scale with CISSECTOR
FitzPatrick, V., Leemans, C., van Arensbergen, J., van Steensel, B., & Bussemaker, H. J. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad232 · Cited by 4
Tonelli, A., Cousin, P., Jankowski, A., Wang, B., Dorier, J., Barraud, J. F., Zunjarrao, S. S., & Gambetta, M. C. (2024) · Developmental Cell · doi:10.1016/j.devcel.2024.10.017 · Cited by 6
Decoding tissue-specific enhancers in plants using massively parallel assays and deep learning
(邓雅欣), Y. D., Zhao, W., (熊逸雪), Y. X., Naeem, M. S., Lu, S., Zhou, X., Zhao, L., & Zhang, L. (2025) · The Plant Cell · doi:10.1093/plcell/koaf236 · Cited by 5
Bridging the variant-to-function gap in type 2 diabetes: advances and challenges
Maynard, A. G., Bhardwaj, R., Jones, T. R., & Claussnitzer, M. (2025) · Diabetologia · doi:10.1007/s00125-025-06600-6 · Cited by 7
The IGVF catalog—from genetic variation to function
Li, D., Liu, S., Assis, P., Li, M., Dong, S., Whaling, I., Jolanki, O., Kagda, M. S., Zhang, W., Macias-Velasco, J. F., et al. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf1341 · Cited by 5
Generative AI for synthetic biology: Designing biological parts, circuits, and genomes
Kim, N., Carluccio, G. D., Zhang, K., & Collins, J. J. (2026) · Cell Systems · doi:10.1016/j.cels.2026.101533 · Cited by 5
Epigenetic regulation of cis-regulatory elements and transcription factors during development
Khan, S., Mishra, R. K., & Srivastava, S. (2023) · Elsevier eBooks · doi:10.1016/b978-0-12-821785-6.00004-9 · Cited by 5
Krchlíková, V., Lu, Y., & Sauter, D. (2025) · Journal of Virology · doi:10.1128/jvi.01351-24 · Cited by 6
Deconstructing the GWAS library: next-generation GWAS
Zhang, W., Koslowski, S., Benzaki, M., Lee, C. J. M., Zhu, Y., Mak, M. C. E., Zhu, Y., Loong, S. S. E., Lettre, G., Anene-Nzelu, C. G., et al. (2025) · Physiological Reviews · doi:10.1152/physrev.00025.2024 · Cited by 5
Deciphering cis -regulatory elements using REgulamentary
Riva, S. G., Sanders, E., Georgiades, E., Venkatesh, S. S., Sergeant, M. J., Gür, E. R., Herrmann, J. C., Baxter, M. D., & Hughes, J. R. (2026) · Bioinformatics Advances · doi:10.1093/bioadv/vbag079 · Cited by 5
López, Y., Vandenbon, A., & Nakai, K. (2014) · PLoS ONE · doi:10.1371/journal.pone.0104342 · Cited by 5
Epigenetic analysis of human postmortem brain tissue
Islam, S. A., Lussier, A. A., & Kobor, M. S. (2018) · Handbook of clinical neurology · doi:10.1016/b978-0-444-63639-3.00017-7 · Cited by 6
Lou, S., Cotter, K. A., Li, T., Liang, J. H., Mohsen, H., Liu, J. J., Zhang, J., Cohen, S. M., Xu, J., Yu, H., et al. (2019) · PLoS Genetics · doi:10.1371/journal.pgen.1007860 · Cited by 4
Emergence of enhancers at late DNA replicating regions
Cornejo‐Páramo, P., Petrova, V., Zhang, X., Young, R. S., & Wong, E. S. W. (2024) · Nature Communications · doi:10.1038/s41467-024-47391-5 · Cited by 6
Precise measurement of molecular phenotypes with barcode-based CRISPRi systems
Lobel, J. H., & Ingolia, N. T. (2025) · Genome biology · doi:10.1186/s13059-025-03610-w · Cited by 4
Transcriptional Dynamics at Brain Enhancers: from Functional Specialization to Neurodegeneration
Vermunt, M. W., & Creyghton, M. P. (2016) · Current Neurology and Neuroscience Reports · doi:10.1007/s11910-016-0689-7 · Cited by 5
United colours of chromatin? Developmental genome organisation in flies
Delandre, C., & Marshall, O. J. (2019) · Biochemical Society Transactions · doi:10.1042/bst20180605 · Cited by 10
Mann, A., & Bhatia, S. (2019) · Biomedicines · doi:10.3390/biomedicines7030071 · Cited by 5
Metadata
- Authors
- Arnold, C. D., Gerlach, D., Stelzer, C., Boryń, Ł. M., Rath, M., & Stark, A.
- Affiliations
- Research Institute of Molecular Pathology (AT)
- Corresponding author
- Stark, Alexander
- Venue
- Science
- Published
- 2013-03
- Volume
- 339
- Issue
- 6123
- Pages
- 1074-1077
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2077874719
- Cited by
- 1,125
- References
- 48
- Citations by year
- 2026: 74 · 2025: 113 · 2024: 107 · 2023: 99 · 2022: 80 · 2021: 96 · 2020: 106 · 2019: 85 · 2018: 77 · 2017: 75 · 2016: 74 · 2015: 64 · 2014: 53 · 2013: 21
- FWCI
- 31.68
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Chromatin Remodeling and Cancer
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene Regulatory Network Analysis
- Keywords
- enhancer activity, STARR-seq, Drosophila, cell type-specific enhancers, transcriptional regulation, gene expression regulation, enhancer screen, developmental regulators
- MeSH terms
- Animals, Chromosome Mapping, Drosophila melanogaster, Enhancer Elements, Genetic, Female, Gene Expression Regulation, HeLa Cells, Humans, Ovary, Transcription, Genetic, Genome, Sequence Analysis, DNA, Gene Expression Regulation, Developmental
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