Discovering motifs in ranked lists of DNA sequences
Open accessAbstract
Computational methods for discovery of sequence elements that are enriched in a target set compared with a background set are fundamental in molecular biology research. One example is the discovery of transcription factor binding motifs that are inferred from ChIP-chip (chromatin immuno-precipitation on a microarray) measurements. Several major challenges in sequence motif discovery still require consideration: (i) the need for a principled approach to partitioning the data into target and background sets; (ii) the lack of rigorous models and of an exact p-value for measuring motif enrichment; (iii) the need for an appropriate framework for accounting for motif multiplicity; (iv) the tendency, in many of the existing methods, to report presumably significant motifs even when applied to randomly generated data. In this paper we present a statistical framework for discovering enriched sequence elements in ranked lists that resolves these four issues. We demonstrate the implementation of this framework in a software application, termed DRIM (discovery of rank imbalanced motifs), which identifies sequence motifs in lists of ranked DNA sequences. We applied DRIM to ChIP-chip and CpG methylation data and obtained the following results. (i) Identification of 50 novel putative transcription factor (TF) binding sites in yeast ChIP-chip data. The biological function of some of them was further investigated to gain new insights on transcription regulation networks in yeast. For example, our discoveries enable the elucidation of the network of the TF ARO80. Another finding concerns a systematic TF binding enhancement to sequences containing CA repeats. (ii) Discovery of novel motifs in human cancer CpG methylation data. Remarkably, most of these motifs are similar to DNA sequence elements bound by the Polycomb complex that promotes histone methylation. Our findings thus support a model in which histone methylation and CpG methylation are mechanistically linked. Overall, we demonstrate that the statistical framework embodied in the DRIM software tool is highly effective for identifying regulatory sequence elements in a variety of applications ranging from expression and ChIP-chip to CpG methylation data. DRIM is publicly available at http://bioinfo.cs.technion.ac.il/drim.
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Embryonic epithelia upregulated genes for developmental processes, while aged epithelia upregulated host-defense programs.
“These were enriched for specialized programs across ages: Embryonic epithelia upregulated genes for developmental processes (Figure 3K, S3K), while aged epithelia upregulated host-defense programs (Figure 3L, FDR q-value < 0.01, GOrilla (Eden et al., 2007, 2009;Baruch et al., 2014).”
From A cellular and spatial map of the choroid plexus across brain ventricles and ages (2021) · cites this paper as Eden et al., 2007
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Gene Ontology: tool for the unification of biology
Ashburner, M., Ball, C. A., Blake, J. A., Botstein, D., Butler, H., Cherry, J. M., Davis, A. P., Dolinski, K., Dwight, S. S., Eppig, J. T., et al. (2000) · Nature Genetics · doi:10.1038/75556 · Cited by 43,206 · see citing works
Fitting a mixture model by expectation maximization to discover motifs in biopolymers.
Bailey, T. L., & Elkan, C. (1994) · PubMed · Cited by 4,933 · see citing works
Transcriptional Regulatory Networks in <i>Saccharomyces cerevisiae</i>
Lee, T. I., Rinaldi, N. J., Robert, F., Odom, D. T., Bar-Joseph, Z., Gerber, G. K., Hannett, N. M., Harbison, C. T., Thompson, C. M., Simon, I., et al. (2002) · Science · doi:10.1126/science.1075090 · Cited by 2,956 · see citing works
Control of Developmental Regulators by Polycomb in Human Embryonic Stem Cells
Lee, T. I., Jenner, R. G., Boyer, L. A., Guenther, M. G., Levine, S. S., Kumar, R., Chevalier, B. S., Johnstone, S. E., Cole, M. F., Isono, K., et al. (2006) · Cell · doi:10.1016/j.cell.2006.02.043 · Cited by 2,238 · see citing works
The Polycomb group protein EZH2 directly controls DNA methylation
Viré, E., Brenner, C., Deplus, R., Blanchon, L., Fraga, M., Didelot, C., Morey, L., Van Eynde, A., Bernard, D., Vanderwinden, J.-M., et al. (2006) · Nature · doi:10.1038/nature04431 · Cited by 2,204 · see citing works
Transcriptional regulatory code of a eukaryotic genome
Harbison, C. T., Gordon, D. B., Lee, T. I., Rinaldi, N. J., MacIsaac, K. D., Danford, T., Hannett, N. M., Tagne, J., Reynolds, D. B., Yoo, J. Y., et al. (2004) · Nature · doi:10.1038/nature02800 · Cited by 2,116 · see citing works
Boyle, E. I., Weng, S., Gollub, J., Jin, H., Botstein, D., Cherry, J. M., & Sherlock, G. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth456 · Cited by 2,067 · see citing works
Molecular classification of cutaneous malignant melanoma by gene expression profiling
Bittner, M. L., Meltzer, P. S., Chen, Y., Jiang, Y. Y., Seftor, E. A., Hendrix, M. J. C., Radmacher, M. D., Simon, R., Zohar Yakhini, B., Ben‐Dor, A., et al. (2000) · Nature · doi:10.1038/35020115 · Cited by 1,989 · see citing works
Genome-Wide Location and Function of DNA Binding Proteins
Ren, B., Robert, F., Wyrick, J. J., Aparicio, O. M., Jennings, E. G., Simon, I., Zeitlinger, J., Schreiber, J., Hannett, N. M., Kanin, E. I., et al. (2000) · Science · doi:10.1126/science.290.5500.2306 · Cited by 1,768 · see citing works
Control of Pancreas and Liver Gene Expression by HNF Transcription Factors
Odom, D. T., Zizlsperger, N., Gordon, D. B., Bell, G. W., Rinaldi, N. J., Murray, H. L., Volkert, T. L., Schreiber, J., Rolfe, A., Gifford, D. K., et al. (2004) · Science · doi:10.1126/science.1089769 · Cited by 1,312 · see citing works
Assessing computational tools for the discovery of transcription factor binding sites
Tompa, M., Li, N., Bailey, T. L., Church, G. M., De Moor, B., Eskin, E., Favorov, A. V., Frith, M. C., Fu, Y., Kent, W. J., et al. (2005) · Nature Biotechnology · doi:10.1038/nbt1053 · Cited by 1,268 · see citing works
Genome-wide mapping of Polycomb target genes unravels their roles in cell fate transitionsPreprint
Bracken, A. P., Dietrich, N., Pasini, D., Hansen, K. H., & Helin, K. (2006) · Genes & Development · doi:10.1101/gad.381706 · Cited by 1,258 · see citing works
Zhang, X., Odom, D. T., Koo, S.-H., Conkright, M. D., Canettieri, G., Best, J., Chen, H., Jenner, R., Herbolsheimer, E., Jacobsen, E., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0501076102 · Cited by 992 · see citing works
Roth, F. P., Hughes, J. D., Estep, P. W., & Church, G. M. (1998) · Nature Biotechnology · doi:10.1038/nbt1098-939 · Cited by 939 · see citing works
BIOPROSPECTOR: DISCOVERING CONSERVED DNA MOTIFS IN UPSTREAM REGULATORY REGIONS OF CO-EXPRESSED GENES
Liu, X., Brutlag, D. L., & Liu, J. S. (2000) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447362_0014 · Cited by 823 · see citing works
Tissue Classification with Gene Expression Profiles
Ben‐Dor, A., Bruhn, L., Friedman, N., Nachman, I., Schummer, M., & Zohar Yakhini, B. (2000) · Journal of Computational Biology · doi:10.1089/106652700750050943 · Cited by 742 · see citing works
Regulatory element detection using correlation with expression
Bussemaker, H. J., Li, H., & Siggia, E. D. (2001) · Nature Genetics · doi:10.1038/84792 · Cited by 721 · see citing works
Liu, X. S., Brutlag, D. L., & Liu, J. S. (2002) · Nature Biotechnology · doi:10.1038/nbt717 · Cited by 670 · see citing works
Buck, M. J., & Lieb, J. D. (2004) · Genomics · doi:10.1016/j.ygeno.2003.11.004 · Cited by 608 · see citing works
Evidence for an instructive mechanism of de novo methylation in cancer cells
Keshet, I., Schlesinger, Y., Farkash, S., Rand, E., Hecht, M., Segal, E., Pikarsky, E., Young, R. A., Niveleau, A., Cedar, H., et al. (2006) · Nature Genetics · doi:10.1038/ng1719 · Cited by 477 · see citing works
Hallikas, O. K., Palin, K., Sinjushina, N., Rautiainen, R., Partanen, J. M., Ukkonen, E., & Taipale, J. (2006) · Cell · doi:10.1016/j.cell.2005.10.042 · Cited by 465 · see citing works
Biotechnological production of 2-phenylethanol
Etschmann, M. M. W., Bluemke, W., Sell, D., & Schrader, J. (2002) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-002-0992-x · Cited by 436 · see citing works
Levine, S. S., Weiss, A., Erdjument‐Bromage, H., Shao, Z., Tempst, P., & Kingston, R. E. (2002) · Molecular and Cellular Biology · doi:10.1128/mcb.22.17.6070-6078.2002 · Cited by 388 · see citing works
Gibbs Recursive Sampler: finding transcription factor binding sites
Thompson, W. A. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg608 · Cited by 318 · see citing works
Computational prediction of transcription-factor binding site locations.
Bulyk, M. L. (2003) · Genome biology · doi:10.1186/gb-2003-5-1-201 · Cited by 307 · see citing works
Predicting aberrant CpG island methylation
Feltus, F. A., Lee, E. K., Costello, J., Plass, C., & Vertino, P. M. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2037852100 · Cited by 278 · see citing works
Genome-Wide Prediction of Polycomb/Trithorax Response Elements in Drosophila melanogaster
Ringrose, L., Rehmsmeier, M., Dura, J., & Paro, R. (2003) · Developmental Cell · doi:10.1016/s1534-5807(03)00337-x · Cited by 261 · see citing works
Sinha, S. (2003) · Nucleic Acids Research · doi:10.1093/nar/gkg618 · Cited by 257 · see citing works
Limitations and potentials of current motif discovery algorithms
Hu, J., Li, Y., & Kihara, D. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki791 · Cited by 240 · see citing works
ANN-SPEC: A METHOD FOR DISCOVERING TRANSCRIPTION FACTOR BINDING SITES WITH IMPROVED SPECIFICITY
Workman, C. T., & Stormo, G. D. (1999) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447331_0044 · Cited by 238 · see citing works
Strutt, H. L., Cavalli, G., & Paro, R. (1997) · The EMBO Journal · doi:10.1093/emboj/16.12.3621 · Cited by 237 · see citing works
Bock, C., Paulsen, M., Tierling, S., Mikeska, T., Lengauer, T., & Walter, J. (2006) · PLoS Genetics · doi:10.1371/journal.pgen.0020026 · Cited by 219 · see citing works
Discovery of novel transcription factor binding sites by statistical overrepresentation
Sinha, S. (2002) · Nucleic Acids Research · doi:10.1093/nar/gkf669 · Cited by 216 · see citing works
Vuralhan, Z., de Morais, M. A., Tai, S. L., Piper, M. D. W., & Pronk, J. T. (2003) · Applied and Environmental Microbiology · doi:10.1128/aem.69.8.4534-4541.2003 · Cited by 206 · see citing works
Modeling dependencies in protein-DNA binding sites
Barash, Y., Elidan, G., Friedman, N., & Kaplan, T. (2003) · Research in Computational Molecular Biology · doi:10.1145/640075.640079 · Cited by 203 · see citing works
A statistical method for finding transcription factor binding sites.
Sinha, S., & Tompa, M. (2000) · PubMed · Cited by 198 · see citing works
Kittleson, M. M., Minhas, K. M., Irizarry, R. A., Ye, S. Q., Edness, G., Breton, E., Conte, J. V., Tomaselli, G. F., Garcia, J. G. N., & Hare, J. M. (2005) · Physiological Genomics · doi:10.1152/physiolgenomics.00255.2004 · Cited by 173 · see citing works
Identification of transcription factor binding sites with variable-order Bayesian networks
Ben‐Gal, I., Shani, A., Gohr, A., Grau, J., Arviv, S., Shmilovici, A., Posch, S., & Große, I. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti410 · Cited by 170 · see citing works
Displaying the in formation contents of structural RNA alignments: the structure logos
Gorodkin, J., Heyer, L. J., Brunak, S., & Storomo, G. D. (1997) · Computer applications in the biosciences · doi:10.1093/bioinformatics/13.6.583 · Cited by 169 · see citing works
Practical Strategies for Discovering Regulatory DNA Sequence Motifs
MacIsaac, K. D., & Fraenkel, E. (2006) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0020036 · Cited by 167 · see citing works
Transcriptional Induction by Aromatic Amino Acids in Saccharomyces cerevisiae
Iraqui, I., VISSERS, S., André, B., & Urrestarazu, A. (1999) · Molecular and Cellular Biology · doi:10.1128/mcb.19.5.3360 · Cited by 143 · see citing works
De novo cis-regulatory module elicitation for eukaryotic genomes
Gupta, M., & Liu, J. S. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0408743102 · Cited by 138 · see citing works
Blaiseau, P.-L., Isnard, A., Surdin-Kerjan, Y., & Thomas, D. (1997) · Molecular and Cellular Biology · doi:10.1128/mcb.17.7.3640 · Cited by 128 · see citing works
Multiple transcriptional activation complexes tether the yeast activator Met4 to DNA
Blaiseau, P.-L., & Thomas, D. (1998) · The EMBO Journal · doi:10.1093/emboj/17.21.6327 · Cited by 122 · see citing works
Oligonucleotide‐based microarray for DNA methylation analysis: Principles and applications
Shi, H., Maier, S., Nimmrich, I., Yan, P. S., Caldwell, C. W., Olek, A., & Huang, T. H. ‐. (2002) · Journal of Cellular Biochemistry · doi:10.1002/jcb.10313 · Cited by 114 · see citing works
Jensen, L. J., & Knudsen, S. (2000) · Bioinformatics · doi:10.1093/bioinformatics/16.4.326 · Cited by 110 · see citing works
Zhu, Z., Pilpel, Y., & Church, G. M. (2002) · Journal of Molecular Biology · doi:10.1016/s0022-2836(02)00026-8 · Cited by 101 · see citing works
A Simple Hyper-Geometric Approach for Discovering Putative Transcription Factor Binding Sites
Barash, Y., Bejerano, G., & Friedman, N. (2001) · Lecture notes in computer science · doi:10.1007/3-540-44696-6_22 · Cited by 94 · see citing works
Mining ChIP-chip data for transcription factor and cofactor binding sites
Smith, A. D., Sumazin, P., Das, D., & Zhang, M. Q. (2005) · Bioinformatics · doi:10.1093/bioinformatics/bti1043 · Cited by 87 · see citing works
J�nger, M., & Thienel, S. (2000) · Software Practice and Experience · doi:10.1002/1097-024x(200009)30:11 · Cited by 86 · see citing works
Anderson, S. F., Steber, C. M., Esposito, R. E., & Coleman, J. E. (1995) · Protein Science · doi:10.1002/pro.5560040918 · Cited by 72 · see citing works
Deremble, C., & Lavery, R. (2005) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2005.01.018 · Cited by 63 · see citing works
Adaptively inferring human transcriptional subnetworks
Das, D., Nahle, Z. A., & Zhang, M. Q. (2006) · Molecular Systems Biology · doi:10.1038/msb4100067 · Cited by 62 · see citing works
A boosting approach for motif modeling using ChIP-chip data
Hong, P., Liu, X. S., Zhou, Q., Lu, X., Liu, J. S., & Wong, W. H. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti402 · Cited by 61 · see citing works
GOLEM: an interactive graph-based gene-ontology navigation and analysis tool
Sealfon, R. S., Hibbs, M. A., Huttenhower, C., Myers, C. L., & Troyanskaya, O. G. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-443 · Cited by 58 · see citing works
Stubb: a program for discovery and analysis of cis-regulatory modules
Sinha, S., Liang, Y., & Siggia, E. D. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl224 · Cited by 55 · see citing works
Ben‐Dor, A., Friedman, N., & Yakhini, Z. (2000) · Cited by 48 · see citing works
Regulatory element detection using correlation with expression (abstract only)
Bussemaker, H. J., Li, H., & Siggia, E. D. (2001) · doi:10.1145/369133.369174 · Cited by 35 · see citing works
Scoring functions for transcription factor binding site prediction
Friberg, M. T., von Rohr, P., & Gonnet, G. H. (2005) · BMC Bioinformatics · doi:10.1186/1471-2105-6-84 · Cited by 24 · see citing works
Nussinov, R. (1986) · Biochimica et Biophysica Acta (BBA) - Gene Structure and Expression · doi:10.1016/0167-4781(86)90106-5 · Cited by 20 · see citing works
Using Expression Data to Discover RNA and DNA Regulatory Sequence Motifs
Zilberstein, C. B.-Z., Eskin, E., & Zohar Yakhini, B. (2005) · Lecture notes in computer science · doi:10.1007/978-3-540-32280-1_7 · Cited by 13 · see citing works
An improved map of conserved regulatory sites for Saccharomyces cerevisiae
MacIsaac, K. D., Wang, T., Gordon, D. B., Gifford, D. K., Stormo, G. D., & Fraenkel, E. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-113 · Cited by 9 · see citing works
Cis-acting sequences that affect the expression of the human fetal gamma-globin genes.
Anagnou, N. P., Moulton, A. D., Keller, G. M., Karlsson, S., Papayannopoulou, T., Stamatoyannopoulos, G., & Nienhuis, A. W. (1985) · PubMed · Cited by 8 · see citing works
Bradford, I., Winter, R. M., Evans, C. R., & Bard, J. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bti017 · Cited by 4 · see citing works
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Molecular and genetic properties of tumors associated with local immune cytolytic activity
Rooney, M. S., Shukla, S. A., Wu, C. J., Getz, G., & Hacohen, N. (2015) · Cell · doi:10.1016/j.cell.2014.12.033 · Cited by 3,825 · see citing works
GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists
Eden, E., Navon, R., Steinfeld, I., Lipson, D., & Yakhini, Z. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-48 · Cited by 3,356 · see citing works
Host microbiota constantly control maturation and function of microglia in the CNS
Erny, D., Hrabě de Angelis, A. L., Jaitin, D., Wieghofer, P., Staszewski, O., David, E., Keren-Shaul, H., Mahlakoiv, T., Jakobshagen, K., Buch, T., et al. (2015) · Nature Neuroscience · doi:10.1038/nn.4030 · Cited by 3,569 · see citing works
Microglia development follows a stepwise program to regulate brain homeostasis
Matcovitch-Natan, O., Winter, D. R., Giladi, A., Vargas Aguilar, S., Spinrad, A., Sarrazin, S., Ben-Yehuda, H., David, E., Zelada González, F., Perrin, P., et al. (2016) · Science · doi:10.1126/science.aad8670 · Cited by 1,180 · see citing works
Reyfman, P. A., Walter, J. M., Joshi, N., Anekalla, K. R., McQuattie-Pimentel, A. C., Chiu, S., Fernandez, R., Akbarpour, M., Chen, C.-I., Ren, Z., et al. (2019) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201712-2410oc · Cited by 1,203 · see citing works
The NASA Twins Study: A multidimensional analysis of a year-long human spaceflight
Garrett-Bakelman, F. E., Darshi, M., Green, S. J., Gur, R. C., Lin, L., Macias, B. R., McKenna, M. J., Meydan, C., Mishra, T., Nasrini, J., et al. (2019) · Science · doi:10.1126/science.aau8650 · Cited by 1,128 · see citing works
Monocyte-derived alveolar macrophages drive lung fibrosis and persist in the lung over the life span
Misharin, A. V., Morales-Nebreda, L., Reyfman, P. A., Cuda, C. M., Walter, J. M., McQuattie-Pimentel, A. C., Chen, C.-I., Anekalla, K. R., Joshi, N., Williams, K. J. N., et al. (2017) · Journal of Experimental Medicine · doi:10.1084/jem.20162152 · Cited by 1,133 · see citing works
RNA-Methylation-Dependent RNA Processing Controls the Speed of the Circadian Clock
Fustin, J., Doi, M., Yamaguchi, Y., Hayashi, H., Nishimura, S., Yoshida, M., Isagawa, T., Morioka, M. S., Kakeya, H., Manabe, I., et al. (2013) · Cell · doi:10.1016/j.cell.2013.10.026 · Cited by 980 · see citing works
Dulak, A. M., Stojanov, P., Peng, S., Lawrence, M. S., Fox, C., Stewart, C., Bandla, S., Imamura, Y., Schumacher, S. E., Shefler, E., et al. (2013) · Nature Genetics · doi:10.1038/ng.2591 · Cited by 736 · see citing works
Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data
McLeay, R. C., & Bailey, T. L. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-165 · Cited by 687 · see citing works
Div-Seq: Single-nucleus RNA-Seq reveals dynamics of rare adult newborn neurons
Habib, N., Li, Y., Heidenreich, M., Swiech, L., Avraham-Davidi, I., Trombetta, J. J., Hession, C., Zhang, F., & Regev, A. (2016) · Science · doi:10.1126/science.aad7038 · Cited by 601 · see citing works
DC isoketal-modified proteins activate T cells and promote hypertension
Kirabo, A., Fontana, V., de Faria, A. P., Loperena, R., Galindo, C. L., Wu, J., Bikineyeva, A. T., Dikalov, S., Xiao, L., Chen, W., et al. (2014) · Journal of Clinical Investigation · doi:10.1172/jci74084 · Cited by 539 · see citing works
Abundant Pleiotropy in Human Complex Diseases and Traits
Sivakumaran, S., Agakov, F. V., Τheodoratou, E., Prendergast, J. G. D., Zgaga, L., Manolio, T. A., Rudan, I., McKeigue, P., Wilson, J. F., & Campbell, H. J. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.10.004 · Cited by 534 · see citing works
Seidlitz, J., Váša, F., Shinn, M., Romero-García, R., Whitaker, K. J., Vértes, P. E., Wagstyl, K., Reardon, P. K., CLASEN, L. S., Liu, S., et al. (2017) · Neuron · doi:10.1016/j.neuron.2017.11.039 · Cited by 488 · see citing works
The Notch and Wnt pathways regulate stemness and differentiation in human fallopian tube organoids
Kessler, M., Hoffmann, K., Brinkmann, V., Thieck, O., Jackisch, S., Toelle, B., Berger, H., Mollenkopf, H., Mangler, M., Sehouli, J., et al. (2015) · Nature Communications · doi:10.1038/ncomms9989 · Cited by 466 · see citing works
A Distinct Gene Module for Dysfunction Uncoupled from Activation in Tumor-Infiltrating T Cells
Singer, M., Wang, C., Cong, L., Marjanovic, N. D., Kowalczyk, M. S., Zhang, H., Nyman, J., Sakuishi, K., Kurtuluş, S., Gennert, D. G., et al. (2016) · Cell · doi:10.1016/j.cell.2016.08.052 · Cited by 414 · see citing works
A Quantitative Tissue-Specific Landscape of Protein Redox Regulation during Aging
Xiao, H., Jedrychowski, M. P., Schweppe, D. K., Huttlin, E. L., Yu, Q., Heppner, D. E., Li, J., Long, J., Mills, E. L., Szpyt, J., et al. (2020) · Cell · doi:10.1016/j.cell.2020.02.012 · Cited by 399 · see citing works
Developmental programming of CpG island methylation profiles in the human genome
Straussman, R., Nejman, D., Roberts, D. N., Steinfeld, I., Blum, B., Benvenisty, N., Simon, I., Zohar Yakhini, B., & Cedar, H. (2009) · Nature Structural & Molecular Biology · doi:10.1038/nsmb.1594 · Cited by 409 · see citing works
Pezzulo, A. A., Starner, T. D., Scheetz, T. E., Traver, G. L., Tilley, A. E., Harvey, B., Crystal, R. G., McCray, P. B., & Zabner, J. (2010) · American Journal of Physiology-Lung Cellular and Molecular Physiology · doi:10.1152/ajplung.00256.2010 · Cited by 390 · see citing works
Benayoun, B. A., Pollina, E. A., Singh, P. P., Mahmoudi, S., Harel, I., Casey, K. M., Dulken, B. W., Kundaje, A., & Brunet, A. (2019) · Genome Research · doi:10.1101/gr.240093.118 · Cited by 360 · see citing works
A cellular and spatial map of the choroid plexus across brain ventricles and ages
Dani, N., Herbst, R. H., McCabe, C., Green, G. S., Kaiser, K., Head, J. P., Cui, J., Shipley, F. B., Jang, A., Dionne, D., et al. (2021) · Cell · doi:10.1016/j.cell.2021.04.003 · Cited by 388 · see citing works
Artemisinins Target GABAA Receptor Signaling and Impair α Cell Identity
Li, J., Casteels, T., Frogne, T., Ingvorsen, C., Honoré, C., Courtney, M. L., Huber, K., Schmitner, N., Kimmel, R. A., Romanov, R. A., et al. (2016) · Cell · doi:10.1016/j.cell.2016.11.010 · Cited by 388 · see citing works
The genomic landscape of nasopharyngeal carcinoma
Lin, D., Meng, X., Hazawa, M., Nagata, Y., Varela, A. M., Xu, L., Sato, Y., Liu, L., Ding, L., Sharma, A., et al. (2014) · Nature Genetics · doi:10.1038/ng.3006 · Cited by 366 · see citing works
Liu, C., Chikina, M. D., Deshpande, R., Menk, A. V., Wang, T., Tabib, T., Brunazzi, E. A., Vignali, K. M., Sun, M., Stolz, D. B., et al. (2019) · Immunity · doi:10.1016/j.immuni.2019.06.017 · Cited by 347 · see citing works
The Fine-Scale and Complex Architecture of Human Copy-Number Variation
Perry, G. H., Ben‐Dor, A., Tsalenko, A., Sampas, N., Rodríguez‐Revenga, L., Tran, C. W., Scheffer-Wong, A., Steinfeld, I., Tsang, P. W. K., Yamada, N. A., et al. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2007.12.010 · Cited by 346 · see citing works
Transcriptomic and cellular decoding of regional brain vulnerability to neurogenetic disorders
Seidlitz, J., Nadig, A., Liu, S., Bethlehem, R. A. I., Vértes, P. E., Morgan, S. E., Váša, F., Romero-García, R., Lalonde, F. M., CLASEN, L. S., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-17051-5 · Cited by 322 · see citing works
DNA methylation profiles of human active and inactive X chromosomesPreprint
Sharp, A. J., Stathaki, E., Migliavacca, E., Brahmachary, M., Montgomery, S. B., Dupré, Y., & Antonarakis, S. E. (2011) · Genome Research · doi:10.1101/gr.112680.110 · Cited by 319 · see citing works
miRNA-mRNA Integrated Analysis Reveals Roles for miRNAs in Primary Breast Tumors
Enerly, E., Steinfeld, I., Sahlberg, K. K., Leivonen, S., Aure, M. R. R., Russnes, H. G., Rønneberg, J. A., Johnsen, H., Navon, R., Rødland, E. A., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016915 · Cited by 306 · see citing works
Kim, K. H., Son, J. M., Benayoun, B. A., & Lee, C. D. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.06.008 · Cited by 311 · see citing works
Martyn, G. E., Wienert, B., Yang, L., Shah, M., Norton, L. J., Burdach, J., Kurita, R., Nakamura, Y., Pearson, R. C. M., Funnell, A. P. W., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0085-0 · Cited by 300 · see citing works
SCINA: A Semi-Supervised Subtyping Algorithm of Single Cells and Bulk Samples
Zhang, Z., Luo, D., Zhong, X. Y., Choi, J. H., Ma, Y., Wang, S., Mahrt, E., Guo, W., Stawiski, E. W., Modrusan, Z. D., et al. (2019) · Genes · doi:10.3390/genes10070531 · Cited by 281 · see citing works
Nrl knockdown by AAV-delivered CRISPR/Cas9 prevents retinal degeneration in mice
Yu, W., Mookherjee, S., Chaitankar, V., Hiriyanna, S., Kim, J.-W., Brooks, M., Ataeijannati, Y., Sun, X., Dong, L., Li, T., et al. (2017) · Nature Communications · doi:10.1038/ncomms14716 · Cited by 271 · see citing works
pH-gated succinate secretion regulates muscle remodeling in response to exercise
Reddy, A., Bozi, L. H. M., Yaghi, O. K., Mills, E. L., Xiao, H., Nicholson, H. E., Paschini, M., Paulo, J. A., Garrity, R., Laznik-Bogoslavski, D., et al. (2020) · Cell · doi:10.1016/j.cell.2020.08.039 · Cited by 279 · see citing works
Detecting microRNA binding and siRNA off-target effects from expression data
van Dongen, S., Abreu‐Goodger, C., & Enright, A. J. (2008) · Nature Methods · doi:10.1038/nmeth.1267 · Cited by 274 · see citing works
Deczkowska, A., Matcovitch-Natan, O., Tsitsou-Kampeli, A., Ben-Hamo, S., Dvir-Szternfeld, R., Spinrad, A., Singer, O., David, E., Winter, D. R., Smith, L. K., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-00769-0 · Cited by 260 · see citing works
The transcriptional landscape of αβ T cell differentiation
Mingueneau, M., Kreslavsky, T., Gray, D. H. D., Heng, T. S. P., Cruse, R., Ericson, J., Bendall, S. C., Spitzer, M. H., Nolan, G. P., Kobayashi, K. S., et al. (2013) · Nature Immunology · doi:10.1038/ni.2590 · Cited by 267 · see citing works
Chen, H.-M., van der Touw, W., Wang, Y. S., Kang, K., Mai, S., Zhang, J., Alsina‐Beauchamp, D., Duty, J. A., Mungamuri, S. K., Zhang, B., et al. (2018) · Journal of Clinical Investigation · doi:10.1172/jci97570 · Cited by 254 · see citing works
Finkbeiner, S. R., Hill, D. R., Altheim, C. H., Dedhia, P. H., Taylor, M. J., Tsai, Y.-H., Chin, A. M., Mahé, M. M., Watson, C. L., Freeman, J. J., et al. (2015) · Stem Cell Reports · doi:10.1016/j.stemcr.2015.04.010 · Cited by 250 · see citing works
ASCL1 reprograms mouse Müller glia into neurogenic retinal progenitors
Pollak, J., Wilken, M. S., Ueki, Y., Cox, K. E., Sullivan, J., Taylor, R. J., Levine, E. M., & Reh, T. A. (2013) · Development · doi:10.1242/dev.091355 · Cited by 243 · see citing works
H3K9me3-heterochromatin loss at protein-coding genes enables developmental lineage specification
Nicetto, D., Donahue, G., Jain, T., Peng, T., Sidoli, S., Sheng, L., Montavon, T., Becker, J. S., Grindheim, J. M., Blahnik, K. R., et al. (2019) · Science · doi:10.1126/science.aau0583 · Cited by 241 · see citing works
A Vertebrate Polycomb Response Element Governs Segmentation of the Posterior Hindbrain
Sing, A., Pannell, D., Karaiskakis, A., Sturgeon, K., Djabali, M., Ellis, J., Lipshitz, H. D., & Cordes, S. P. (2009) · Cell · doi:10.1016/j.cell.2009.08.020 · Cited by 237 · see citing works
Duodenum Intestine-Chip for preclinical drug assessment in a human relevant model
Kasendra, M. J., Luc, R., Yin, J., Manatakis, D. V., Kulkarni, G., Lucchesi, C., Sliz, J. D., Apostolou, A. P., Sunuwar, L., Obrigewitch, J., et al. (2020) · eLife · doi:10.7554/elife.50135 · Cited by 227 · see citing works
Vértes, P. E., Rittman, T., Whitaker, K. J., Romero-García, R., Váša, F., Kitzbichler, M. G., Wagstyl, K., Fonagy, P., Dolan, R. J., Jones, P. B., et al. (2016) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2015.0362 · Cited by 200 · see citing works
MoMo: discovery of statistically significant post-translational modification motifs
Cheng, A., Grant, C. E., Noble, W. S., & Bailey, T. L. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty1058 · Cited by 204 · see citing works
Hu, Z., Artibani, M., Alsaadi, A., Wietek, N. C., Morotti, M., Shi, T., Zhong, Z., González, L. S., El-Sahhar, S., Carrami, E. M., et al. (2020) · Cancer Cell · doi:10.1016/j.ccell.2020.01.003 · Cited by 189 · see citing works
VDAC2 enables BAX to mediate apoptosis and limit tumor development
Chin, H. S., Li, M. X., Tan, I. K. L., Ninnis, R. L., Reljic, B., Scicluna, K., Dagley, L. F., Sandow, J. J., Kelly, G. L., Samson, A. L., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-07309-4 · Cited by 196 · see citing works
Dynamics of DNA Methylation in Recent Human and Great Ape Evolution
Hernando-Herraez, I., Prado-Martinez, J., Garg, P., Fernández-Callejo, M., Heyn, H., Hvilsom, C., Navarro, A., Esteller, M., Sharp, A. J., & Marquès‐Bonet, T. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003763 · Cited by 200 · see citing works
Bock, C., & Lengauer, T. (2008) · Bioinform. · doi:10.1093/bioinformatics/btm546 · Cited by 184 · see citing works
A Model-Based Approach for Identifying Signatures of Ancient Balancing Selection in Genetic Data
DeGiorgio, M., Lohmueller, K. E., & Nielsen, R. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004561 · Cited by 187 · see citing works
Watson, C. T., Szutorisz, H., Garg, P., Martin, Q., Landry, J. A., Sharp, A. J., & Hurd, Y. L. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.155 · Cited by 182 · see citing works
scDART-seq reveals distinct m6A signatures and mRNA methylation heterogeneity in single cells
Tegowski, M., Flamand, M. N., & Meyer, K. D. (2022) · Molecular Cell · doi:10.1016/j.molcel.2021.12.038 · Cited by 182 · see citing works
Blank, T., Detje, C. N., Spieß, A., Hagemeyer, N., Brendecke, S. M., Wolfart, J., Staszewski, O., Zöller, T., Papageorgiou, I. E., Schneider, J., et al. (2016) · Immunity · doi:10.1016/j.immuni.2016.04.005 · Cited by 179 · see citing works
Identifying drug targets in tissues and whole blood with thermal-shift profiling
Perrin, J., Werner, T., Kurzawa, N., Rutkowska, A., Childs, D. D., Kalxdorf, M., Poeckel, D., Stonehouse, E., Strohmer, K., Heller, B., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-019-0388-4 · Cited by 178 · see citing works
Stability and aggregation of ranked gene lists
Boulesteix, A., & Slawski, M. (2009) · Briefings in Bioinformatics · doi:10.1093/bib/bbp034 · Cited by 180 · see citing works
Gutiérrez‐Arcelus, M., Teslovich, N. C., Mola, A. R., Polidoro, R. B., Nathan, A., Kim, H., Hannes, S. K., Slowikowski, K., Watts, G. F. M., Korsunsky, I., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-08604-4 · Cited by 177 · see citing works
Braten, O., Livneh, I., Ziv, T., Admon, A., Kehat, I., Caspi, L. H., Gonen, H., Bercovich, B., Godzik, A., Jahandideh, S. S., et al. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1608644113 · Cited by 169 · see citing works
Single-cell RNA sequencing of human liver reveals hepatic stellate cell heterogeneity
Payen, V. L., Lavergne, A., Alevra Sarika, N., Colonval, M., Karim, L., Deckers, M., Najimi, M., Coppieters, W., Charloteaux, B., Sokal, E. M., et al. (2021) · JHEP Reports · doi:10.1016/j.jhepr.2021.100278 · Cited by 160 · see citing works
Cancer cells enter dormancy after cannibalizing mesenchymal stem/stromal cells (MSCs)
Bartosh, T. J., Ullah, M., Zeitouni, S., Beaver, J., & Prockop, D. J. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1612290113 · Cited by 164 · see citing works
PASTAA: identifying transcription factors associated with sets of co-regulated genes
Roider, H. G., Manke, T., O'Keeffe, S., Vingron, M., & Haas, S. A. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btn627 · Cited by 154 · see citing works
Lee, B., Bhinge, A., & Iyer, V. R. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1313 · Cited by 148 · see citing works
Marttila, S., Kananen, L., Häyrynen, S., Jylhävä, J., Nevalainen, T., Hervonen, A., Jylhä, M. K., Nykter, M., & Hurme, M. (2015) · BMC Genomics · doi:10.1186/s12864-015-1381-z · Cited by 151 · see citing works
Wright, A. E., Darolti, I., Bloch, N. I., Oostra, V., Sandkam, B. A., Buechel, S. D., Kolm, N., Breden, F. J., Viçoso, B., & Mank, J. E. (2017) · Nature Communications · doi:10.1038/ncomms14251 · Cited by 148 · see citing works
Frakes, A. E., Metcalf, M. G., Tronnes, S. U., Bar‐Ziv, R., Durieux, J., Gildea, H. K., Kandahari, N., Monshietehadi, S., & Dillin, A. G. (2020) · Science · doi:10.1126/science.aaz6896 · Cited by 146 · see citing works
Identification of Driver and Passenger DNA Methylation in Cancer by Epigenomic Analysis
Kalari, S. K., & Pfeifer, G. P. (2010) · Advances in genetics · doi:10.1016/b978-0-12-380866-0.60010-1 · Cited by 141 · see citing works
kpLogo: positional k-mer analysis reveals hidden specificity in biological sequences
Wu, X., & Bartel, D. P. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx323 · Cited by 140 · see citing works
Tennessen, J. M., Bertagnolli, N. M., Evans, J. M., Sieber, M., Cox, J. E., & Thummel, C. S. (2014) · G3 Genes Genomes Genetics · doi:10.1534/g3.114.010652 · Cited by 141 · see citing works
Transcriptome Profiling of the Murine Testis during the First Wave of Spermatogenesis
Laiho, A., Kotaja, N., Gyenesei, A., & Sironen, A. I. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061558 · Cited by 138 · see citing works
de Porras, V. R., Bystrup, S., Martínez‐Cardús, A., Pluvinet, R., Sumoy, L., Howells, L. M., James, M. I., Iwuji, C., Manzano, J. L., Layos, L., et al. (2016) · Scientific Reports · doi:10.1038/srep24675 · Cited by 136 · see citing works
Avoiding the pitfalls of gene set enrichment analysis with SetRank
Simillion, C., Liechti, R., Lischer, H. E. L., Ioannidis, V., & Bruggmann, R. (2017) · BMC Bioinformatics · doi:10.1186/s12859-017-1571-6 · Cited by 131 · see citing works
Barker, B. M., Kroll, K., Vödisch, M., Mazurie, A., Kniemeyer, O., & Cramer, R. A. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-62 · Cited by 127 · see citing works
Tahiri, A., Leivonen, S., Lüders, T., Steinfeld, I., Aure, M. R. R., Geisler, J., Mäkelä, R., Nord, S., Riis, M. L. H., Zohar Yakhini, B., et al. (2013) · Carcinogenesis · doi:10.1093/carcin/bgt333 · Cited by 125 · see citing works
Betzel, R. F., Medaglia, J. D., Kahn, A. E., Soffer, J., Schonhaut, D. R., & Bassett, D. S. (2019) · Nature Biomedical Engineering · doi:10.1038/s41551-019-0404-5 · Cited by 128 · see citing works
Masculinization of Gene Expression Is Associated with Exaggeration of Male Sexual Dimorphism
Pointer, M. A., Harrison, P. W., Wright, A. E., & Mank, J. E. (2013) · PLoS Genetics · doi:10.1371/journal.pgen.1003697 · Cited by 127 · see citing works
The activity-dependent histone variant H2BE modulates the life span of olfactory neurons
Santoro, S. W., & Dulac, C. G. (2012) · eLife · doi:10.7554/elife.00070 · Cited by 122 · see citing works
Campbell, C., Dikiy, S., Bhattarai, S. K., Chinen, T., Matheis, F., Calafiore, M., Hoyos, B. E., Hanash, A. M., Mucida, D., Bucci, V., et al. (2018) · Immunity · doi:10.1016/j.immuni.2018.04.013 · Cited by 118 · see citing works
The Hyaluronidase, TMEM2, Promotes ER Homeostasis and Longevity Independent of the UPRER
Schinzel, R. T., Higuchi‐Sanabria, R., Shalem, O., Moehle, E. A., Webster, B. M., Joe, L. K., Bar‐Ziv, R., Frankino, P. A., Durieux, J., Pender, C. L., et al. (2019) · Cell · doi:10.1016/j.cell.2019.10.018 · Cited by 115 · see citing works
Blood pressure regulation by CD4+ lymphocytes expressing choline acetyltransferase
Olofsson, P. S., Steinberg, B. E., Sobbi, R., Cox, M. A., Ahmed, M. N., Oswald, M., Szekeres, F. L. M., Hanes, W. M., Introini, A., Liu, S. F., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3663 · Cited by 115 · see citing works
Tail Bud Progenitor Activity Relies on a Network Comprising Gdf11, Lin28, and Hox13 Genes
Aires, R., de Lemos, L., Nóvoa, A., Jurberg, A. D., Mascrez, B., Duboule, D., & Mallo, M. (2019) · Developmental Cell · doi:10.1016/j.devcel.2018.12.004 · Cited by 113 · see citing works
Merging transcriptomics and metabolomics - advances in breast cancer profiling
Borgan, E., Sitter, B., Lingjærde, O. C., Johnsen, H., Lundgren, S., Bathen, T. F., Sørlie, T., Børresen‐Dale, A., & Gribbestad, I. S. (2010) · BMC Cancer · doi:10.1186/1471-2407-10-628 · Cited by 112 · see citing works
Chromatin features constrain structural variation across evolutionary timescales
Fudenberg, G., & Pollard, K. S. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1808631116 · Cited by 106 · see citing works
Variation in promiscuity and sexual selection drives avian rate of Faster‐Z evolution
Wright, A. E., Harrison, P. W., Zimmer, F., Montgomery, S. H., Pointer, M. A., & Mank, J. E. (2015) · Molecular Ecology · doi:10.1111/mec.13113 · Cited by 106 · see citing works
Marquer, C., Lainé, J., Dauphinot, L., Hanbouch, L., Lemercier-Neuillet, C., Pierrot, N., Bossers, K., Le, M., Corlier, F. W., Benstaali, C., et al. (2014) · Molecular Neurodegeneration · doi:10.1186/1750-1326-9-60 · Cited by 101 · see citing works
Regulation of lipids is central to replicative senescence
Lizardo, D. Y., Lin, Y., Gökçümen, Ö., & Atilla‐Gokcumen, G. E. (2017) · Molecular BioSystems · doi:10.1039/c6mb00842a · Cited by 100 · see citing works
A Feature-Based Approach to Modeling Protein–DNA Interactions
Sharon, E., Lubliner, S., & Segal, E. (2008) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000154 · Cited by 101 · see citing works
DAZL Limits Pluripotency, Differentiation, and Apoptosis in Developing Primordial Germ Cells
Chen, H.-H., Welling, M., Bloch, D. B., Muñoz, J., Mientjes, E., Chen, X., Tramp, C. A., Wu, J., Yabuuchi, A., Chou, Y., et al. (2014) · Stem Cell Reports · doi:10.1016/j.stemcr.2014.09.003 · Cited by 100 · see citing works
DNA replication stress restricts ribosomal DNA copy number
Salim, D., Bradford, W. D., Freeland, A. L., Cady, G. K., Wang, J., Pruitt, S. C., & Gerton, J. L. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1007006 · Cited by 97 · see citing works
An energy costly architecture of neuromodulators for human brain evolution and cognition
Castrillón, G., Epp, S. M., Bose, A., Fraticelli, L., Hechler, A., Belenya, R., Ranft, A., Yakushev, I. Y., Utz, L., Sundar, L. K. S., et al. (2023) · Science Advances · doi:10.1126/sciadv.adi7632 · Cited by 97 · see citing works
Li, L. (2009) · Journal of Computational Biology · doi:10.1089/cmb.2008.16tt · Cited by 97 · see citing works
Finding the target sites of RNA ‐binding proteins
Li, X., Kazan, H., Lipshitz, H. D., & Morris, Q. (2013) · Wiley Interdisciplinary Reviews - RNA · doi:10.1002/wrna.1201 · Cited by 91 · see citing works
Tri-methylation of histone H3 lysine 4 facilitates gene expression in ageing cells
Cruz, C., Rosa, M. D., Krueger, C., Gao, Q., Horkai, D., King, M. R., Field, L., & Houseley, J. M. (2018) · eLife · doi:10.7554/elife.34081 · Cited by 95 · see citing works
Schmidt, S., Gay, D. M., Uthe, F. W., Denk, S., Paauwe, M., Matthes, N., Diefenbacher, M. E., Bryson, S., Warrander, F., Erhard, F., et al. (2019) · Nature Cell Biology · doi:10.1038/s41556-019-0408-0 · Cited by 94 · see citing works
Lotsberg, M. L., Wnuk-Lipińska, K., Terry, S., Tan, T. Z., Lü, N., Trachsel-Moncho, L., Røsland, G. V., Siraji, M. I., Hellesøy, M., Rayford, A. J., et al. (2020) · Journal of Thoracic Oncology · doi:10.1016/j.jtho.2020.01.015 · Cited by 95 · see citing works
Berr, A. L., Wiese, K. M., dos Santos, G., Koch, C. M., Anekalla, K. R., Kidd, M. E., Davis, J. M., Cheng, Y., Hu, Y., & Ridge, K. M. (2023) · Oncogene · doi:10.1038/s41388-023-02703-9 · Cited by 94 · see citing works
Cistrome-GO: a web server for functional enrichment analysis of transcription factor ChIP-seq peaks
Li, S., Wan, C., Zheng, R., Fan, J., Dong, X., Meyer, C. A., & Liu, X. S. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz332 · Cited by 93 · see citing works
Combinatorial prediction of marker panels from single‐cell transcriptomic data
Delaney, C., Schnell, A., Cammarata, L. V., Yao-Smith, A., Regev, A., Kuchroo, V. K., & Singer, M. (2019) · Molecular Systems Biology · doi:10.15252/msb.20199005 · Cited by 86 · see citing works
Expression of CDK8 and CDK8-interacting Genes as Potential Biomarkers in Breast Cancer
Broude, E. V., Győrffy, B., Chumanevich, A. A., Chen, M., McDermott, M. S. J., Shtutman, M. S., Catroppo, J. F., & Roninson, I. B. (2015) · Current Cancer Drug Targets · doi:10.2174/156800961508151001105814 · Cited by 90 · see citing works
Tcf21 regulates the specification and maturation of proepicardial cells
Tandon, P., Miteva, Y., Kuchenbrod, L. M., Cristea, I. M., & Conlon, F. L. (2013) · Development · doi:10.1242/dev.093385 · Cited by 88 · see citing works
Growth of the Developing Cerebral Cortex Is Controlled by MicroRNA-7 through the p53 Pathway
Pollock, A., Bian, S., Zhang, C., Chen, Z., & Sun, T. (2014) · Cell Reports · doi:10.1016/j.celrep.2014.04.003 · Cited by 88 · see citing works
Evidence-ranked motif identification
Georgiev, S., Boyle, A. P., Jayasurya, K., Ding, X., Mukherjee, S., & Ohler, U. (2010) · Genome Biology · doi:10.1186/gb-2010-11-2-r19 · Cited by 98 · see citing works
Keam, S. P., Sobala, A., ten Have, S., & Hutvágner, G. (2016) · Journal of Proteome Research · doi:10.1021/acs.jproteome.6b00267 · Cited by 87 · see citing works
- Authors
- Eden, E., Lipson, D., Yogev, S., & Yakhini, Z.
- Affiliations
- Technion – Israel Institute of Technology (IL)
- Corresponding author
- Eden, Eran
- ORCID
- Lipson, Doron
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2007-03-23
- Volume
- 3
- Issue
- 3
- Pages
- e39
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC1829477
- OpenAlex
- W1981093360
- Cited by
- 696
- References
- 65
- Citations by year
- 2026: 18 · 2025: 25 · 2024: 23 · 2023: 44 · 2022: 42 · 2021: 80 · 2020: 54 · 2019: 57 · 2018: 53 · 2017: 52 · 2016: 53 · 2015: 36 · 2014: 31 · 2013: 41 · 2012: 22
- FWCI
- 6.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- Hebrew University of Jerusalem
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- motif discovery, ranked lists, transcription factor binding sites, ChIP-chip, CpG methylation, motif enrichment, Polycomb complexes, histone methylation, CA repeats
- MeSH terms
- Algorithms, Base Sequence, Molecular Sequence Data, Regulatory Sequences, Nucleic Acid, Sequence Homology, Nucleic Acid, Software, Sequence Alignment, Conserved Sequence, Sequence Analysis, DNA, CpG Islands, DNA Methylation, Chromatin Immunoprecipitation
About these checks
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