FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482

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

The control of the false discovery rate in multiple testing under dependency

Benjamini, Y., & Yekutieli, D. (2001) · The Annals of Statistics · doi:10.1214/aos/1013699998 · Cited by 10,490

Identifying differentially expressed genes using false discovery rate controlling procedures

Reiner, A., Yekutieli, D., & Benjamini, Y. (2003) · Bioinformatics · doi:10.1093/bioinformatics/btf877 · Cited by 1,765

Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources

Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nature Protocols · doi:10.1038/nprot.2008.211 · Cited by 35,890

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

Huang, D. W., Sherman, B. T., & Lempicki, R. A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkn923 · Cited by 14,108

Enrichr: a comprehensive gene set enrichment analysis web server 2016 update

Kuleshov, M. V., Jones, M. R., Rouillard, A. D., Fernandez, N. F., Duan, Q., Wang, Z., Koplev, S., Jenkins, S. L., Jagodnik, K. M., Lachmann, A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw377 · Cited by 10,799

Multiplexed protein quantitation in Saccharomyces cerevisiae using amine-reactive isobaric tagging reagents

Ross, P. L., Huang, Y. N., Marchese, J. N., Williamson, B., Parker, K., Hattan, S., Khainovski, N., Pillai, S., Dey, S., Daniels, S., et al. (2004) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m400129-mcp200 · Cited by 4,401

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

agriGO: a GO analysis toolkit for the agricultural community

Du, Z., Zhou, X., Ling, Y., Zhang, Z., & Su, Z. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq310 · Cited by 2,396

Identification of Mammalian microRNA Host Genes and Transcription Units

Rodriguez, A., Griffiths-Jones, S., Ashurst, J. L., & Bradley, A. (2004) · Genome Research · doi:10.1101/gr.2722704 · Cited by 2,128

GO::TermFinder–open source software for accessing gene ontology information and finding significantly enriched gene ontology terms associated with a list of genes

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

Improved human disease candidate gene prioritization using mouse phenotype

Chen, J., Xu, H., Aronow, B. J., & Jegga, A. G. (2007) · BMC Bioinformatics · doi:10.1186/1471-2105-8-392 · Cited by 284

BRANCHED1 Promotes Axillary Bud Dormancy in Response to Shade in Arabidopsis

González-Grandío, E., Poza-Carrión, C., Sorzano, C. O. S., & Cubas, P. (2013) · The Plant Cell · doi:10.1105/tpc.112.108480 · Cited by 272

Null mutations in human and mouse orthologs frequently result in different phenotypes

Liao, B.-Y., & Zhang, J. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0800387105 · Cited by 234

PU.1 target genes undergo Tet2-coupled demethylation and DNMT3b-mediated methylation in monocyte-to-osteoclast differentiation

de la Rica, L., Rodríguez-Ubreva, J., García, M., Islam, A. B., Urquiza, J. M., Hernando, H., Christensen, J., Helin, K., Gómez-Vaquero, C., & Ballestar, E. (2013) · Genome Biology · doi:10.1186/gb-2013-14-9-r99 · Cited by 211

Characterization of genome-wide p53-binding sites upon stress response

Smeenk, L., van Heeringen, S. J., Koeppel, M., van Driel, M. A., Bartels, S. J. J., Akkers, R. C., Denissov, S., Stunnenberg, H. G., & Lohrum, M. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn232 · Cited by 211

The peroxisome proliferator-activated receptor γ coactivator 1α/β (PGC-1) coactivators repress the transcriptional activity of NF-κB in skeletal muscle cells

Eisele, P. S., Salatino, S., Sobek, J., Hottiger, M. O., & Handschin, C. (2013) · Journal of Biological Chemistry · doi:10.1074/jbc.m112.375253 · Cited by 187

Data Integration Challenges for Machine Learning in Precision Medicine

Martínez-García, M., & Hernández-Lemus, E. (2022) · Frontiers in Medicine · doi:10.3389/fmed.2021.784455 · Cited by 185

Senescence-associated ribosome biogenesis defects contributes to cell cycle arrest through the Rb pathway

Lessard, F., Igelmann, S., Trahan, C., Huot, G., Saint-Germain, E., Mignacca, L., Del Toro, N., Lopes-Paciencia, S., Le Calvé, B., Montero, M., et al. (2018) · Nature Cell Biology · doi:10.1038/s41556-018-0127-y · Cited by 174

Primary and secondary transcriptional effects in the developing human down syndrome brain and heart

Mao, R., Wang, X., Spitznagel, E. L., Frelin, L. P., Ting, J. C., Ding, H., Kim, J.-W., Ruczinski, I., Downey, T. J., & Pevsner, J. (2005) · Genome Biology · doi:10.1186/gb-2005-6-13-r107 · Cited by 166

Gene gain and loss across the metazoan tree of life

Fernández, R., & Gabaldón, T. (2020) · Nature Ecology & Evolution · doi:10.1038/s41559-019-1069-x · Cited by 165

The proinflammatory cytokine-induced IRG1 protein associates with mitochondria

Degrandi, D., Hoffmann, R., Beuter-Gunia, C., & Pfeffer, K. (2009) · Journal of Interferon & Cytokine Research · doi:10.1089/jir.2008.0013 · Cited by 155

Global analysis of in vivo Foxa2-binding sites in mouse adult liver using massively parallel sequencing

Wederell, E. D., Bilenky, M., Cullum, R., Thiessen, N., Dagpinar, M., Delaney, A., Varhol, R., Zhao, Y., Zeng, T., Bernier, B., et al. (2008) · Nucleic Acids Research · doi:10.1093/nar/gkn382 · Cited by 150

The acquisition of resistance to TNFα in breast cancer cells is associated with constitutive activation of autophagy as revealed by a transcriptome analysis using a custom microarray

Moussay, E., Kaoma, T., Baginska, J., Muller, A., Van Moer, K., Nicot, N., Nazarov, P. V., Vallar, L., Chouaib, S., Berchem, G., et al. (2011) · Autophagy · doi:10.4161/auto.7.7.15454 · Cited by 125

Proteomics-Based Methods for Discovery, Quantification, and Validation of Protein–Protein Interactions

Miteva, Y. V., Budayeva, H. G., & Cristea, I. M. (2013) · Analytical Chemistry · doi:10.1021/ac3033257 · Cited by 105

Genome-wide Analysis of Alternative Pre-mRNA Splicing and RNA-Binding Specificities of the Drosophila hnRNP A/B Family Members

Blanchette, M., Green, R. E., MacArthur, S., Brooks, A. N., Brenner, S. E., Eisen, M. B., & Rio, D. C. (2009) · Molecular Cell · doi:10.1016/j.molcel.2009.01.022 · Cited by 86

Text Mining for Metabolic Pathways, Signaling Cascades, and Protein Networks

Hoffmann, R., Krallinger, M., Andres, E., Tamames, J., Blaschke, C., & Valencia, A. (2005) · Science's STKE · doi:10.1126/stke.2832005pe21 · Cited by 88

The Corepressor NCoR1 Antagonizes PGC-1 α and Estrogen-Related Receptor α in the Regulation of Skeletal Muscle Function and Oxidative Metabolism

Pérez-Schindler, J., Summermatter, S., Salatino, S., Zorzato, F., Beer, M., Balwierz, P. J., van Nimwegen, E., Feige, J. N., Auwerx, J., & Handschin, C. (2012) · Molecular and Cellular Biology · doi:10.1128/mcb.00877-12 · Cited by 82

Pathway analysis of dilated cardiomyopathy using global proteomic profiling and enrichment maps

Isserlin, R., Merico, D., Alikhani‐Koupaei, R., Gramolini, A., Bader, G. D., & Emili, A. (2010) · PROTEOMICS · doi:10.1002/pmic.200900412 · Cited by 63

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

Transcriptomic Analysis Identifies Growth Rate Modulation as a Component of the Adaptation of Mycobacteria to Survival inside the Macrophage

Beste, D. J. V., Laing, E., Bonde, B., Avignone-Rossa, C., Bushell, M. E., & McFadden, J. J. (2007) · Journal of Bacteriology · doi:10.1128/jb.01787-06 · Cited by 55

Transcriptional network analysis in muscle reveals AP-1 as a partner of PGC-1α in the regulation of the hypoxic gene program

Baresic, M., Salatino, S., Kupr, B., van Nimwegen, E., & Handschin, C. (2014) · Molecular and Cellular Biology · doi:10.1128/mcb.01710-13 · Cited by 40

PAGER: constructing PAGs and new PAG-PAG relationships for network biology

Yue, Z., Kshirsagar, M. M., Nguyen, T., Suphavilai, C., Neylon, M. T., Zhu, L., Ratliff, T., & Chen, J. Y. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv265 · Cited by 30

GOAT: An R Tool for Analysing Gene Ontology??? Term Enrichment

Xu, Q., & Shaulsky, G. (2005) · Applied Bioinformatics · doi:10.2165/00822942-200504040-00008 · Cited by 19