Cluster analysis and display of genome-wide expression patterns

Hypoxia-induced gene expression profiling in the euryoxic fish Gillichthys mirabilis

Gracey, A. Y., Troll, J. V., & Somero, G. N. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.98.4.1993 · Cited by 561

Coordination of Growth Rate, Cell Cycle, Stress Response, and Metabolic Activity in Yeast

Brauer, M. J., Huttenhower, C., Airoldi, E. M., Rosenstein, R., Matese, J. C., Gresham, D., Boer, V. M., Troyanskaya, O. G., & Botstein, D. (2008) · Molecular Biology of the Cell · doi:10.1091/mbc.e07-08-0779 · Cited by 558

Genomic Expression Responses to DNA-damaging Agents and the Regulatory Role of the Yeast ATR Homolog Mec1p

Gasch, A. P., Huang, M., Metzner, S., Botstein, D., Elledge, S. J., & Brown, P. O. (2001) · Molecular Biology of the Cell · doi:10.1091/mbc.12.10.2987 · Cited by 542

Large Expression Differences in Genes for Iron and Zinc Homeostasis, Stress Response, and Lignin Biosynthesis Distinguish Roots of Arabidopsis thaliana and the Related Metal Hyperaccumulator Thlaspi caerulescens

van de Mortel, J. E., Almar Villanueva, L., Schat, H., Kwekkeboom, J., Coughlan, S., Moerland, P. D., Ver Loren van Themaat, E., Koornneef, M., & Aarts, M. G. M. (2006) · Plant Physiology · doi:10.1104/pp.106.082073 · Cited by 547

'Gene shaving' as a method for identifying distinct sets of genes with similar expression patterns

Hastie, T., Tibshirani, R., Eisen, M. B., Alizadeh, A., Levy, R., Staudt, L., Chan, W. C., Botstein, D., & Brown, P. (2000) · Genome Biology · doi:10.1186/gb-2000-1-2-research0003 · Cited by 547

Members of the H3K4 trimethylation complex regulate lifespan in a germline-dependent manner in C. elegans

Greer, E. L., Maures, T. J., Hauswirth, A. G., Green, E. M., Leeman, D. S., Maro, G. S., Han, S., Banko, M. R., Gozani, O., & Brunet, A. (2010) · Nature · doi:10.1038/nature09195 · Cited by 543

CRISPR Interference-Based Platform for Multimodal Genetic Screens in Human iPSC-Derived Neurons

Tian, R., Gachechiladze, M. A., Ludwig, C. H., Laurie, M. T., Hong, J. Y., Nathaniel, D., Prabhu, A. V., Fernandopulle, M. S., Patel, R., Abshari, M., et al. (2019) · Neuron · doi:10.1016/j.neuron.2019.07.014 · Cited by 543

A motif-based profile scanning approach for genome-wide prediction of signaling pathways

Yaffe, M. B., Leparc, G. G., Lai, J., Obata, T., Volinia, S., & Cantley, L. C. (2001) · Nature Biotechnology · doi:10.1038/86737 · Cited by 517

Tumor Suppressor and Aging Biomarker p16INK4a Induces Cellular Senescence without the Associated Inflammatory Secretory Phenotype

Coppé, J.-P., Rodier, F., Patil, C. K., Freund, A., Desprez, P.-Y., & Campisi, J. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.257071 · Cited by 506

Large-Scale Delineation of Secreted Protein Biomarkers Overexpressed in Cancer Tissue and Serum

Welsh, J. B., Sapinoso, L. M., Kern, S. G., Brown, D. A., Liu, T., Bauskin, A. R., Ward, R. L., Hawkins, N. J., Quinn, D. I., Russell, P. J., et al. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0530278100 · Cited by 503

Global Survey of Organ and Organelle Protein Expression in Mouse: Combined Proteomic and Transcriptomic Profiling

Kislinger, T., Cox, B., Kannan, A., Chung, C., Hu, P., Ignatchenko, A., Scott, M. S., Gramolini, A. O., Morris, Q., Hallett, M. T., et al. (2006) · Cell · doi:10.1016/j.cell.2006.01.044 · Cited by 482

Epithelial versus Mesenchymal Phenotype Determines In vitro Sensitivity and Predicts Clinical Activity of Erlotinib in Lung Cancer Patients

Yauch, R. L., Januario, T., Eberhard, D. A., Cavet, G., Zhu, W., Fu, L., Pham, T. Q., Soriano, R., Stinson, J., Seshagiri, S., et al. (2005) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-05-1492 · Cited by 495

Elevated gene expression levels distinguish human from non-human primate brains

Cáceres, M., Lachuer, J., Zapala, M. A., Redmond, J. C., Kudo, L., Geschwind, D. H., Lockhart, D. J., Preuss, T. M., & Barlow, C. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2135499100 · Cited by 491

Bootstrapping cluster analysis: Assessing the reliability of conclusions from microarray experiments

Kerr, M. K., & Churchill, G. A. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.161273698 · Cited by 474

TMPRSS2:ETV4 Gene Fusions Define a Third Molecular Subtype of Prostate Cancer

Tomlins, S. A., Mehra, R., Rhodes, D. R., Smith, L. R., Roulston, D., Helgeson, B. E., Cao, X., Wei, J. T., Rubin, M. A., Shah, R. B., et al. (2006) · Cancer Research · doi:10.1158/0008-5472.can-06-0168 · Cited by 469

Comparison of co-expression measures: mutual information, correlation, and model based indices

Song, L., Langfelder, P., & Horvath, S. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-328 · Cited by 460

Granulocytes govern the transcriptional response, morphology and proliferation of Candida albicans in human blood

Fradin, C., De Groot, P., MacCallum, D., Schaller, M., Klis, F., Odds, F. C., & Hube, B. (2005) · Molecular Microbiology · doi:10.1111/j.1365-2958.2005.04557.x · Cited by 455

Gene expression patterns in human placenta

Sood, R., Zehnder, J. L., Druzin, M. L., & Brown, P. O. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0508035103 · Cited by 454

Understanding network concepts in modules

Dong, J., & Horvath, S. (2007) · BMC Systems Biology · doi:10.1186/1752-0509-1-24 · Cited by 455

A human-like senescence-associated secretory phenotype is conserved in mouse cells dependent on physiological oxygen.

Coppé, J.-P., Patil, C. K., Rodier, F., Krtolica, A., Beauséjour, C. M., Parrinello, S., Hodgson, J. G., Chin, K., Desprez, P.-Y., & Campisi, J. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009188 · Cited by 455

A clinical microchip for evaluation of single immune cells reveals high functional heterogeneity in phenotypically similar T cells

Ma, C., Fan, R., Ahmad, H., Shi, Q., Comin-Anduix, B., Chodon, T., Koya, R. C., Liu, C.-C., Kwong, G. A., Radu, C. G., et al. (2011) · Nature Medicine · doi:10.1038/nm.2375 · Cited by 441

A HIF1α Regulatory Loop Links Hypoxia and Mitochondrial Signals in Pheochromocytomas

Dahia, P. L. M., Ross, K. N., Wright, M. E., Hayashida, C. Y., Santagata, S., Barontini, M., Kung, A. L., Sanso, G., Powers, J. F., Tischler, A. S., et al. (2005) · PLoS Genetics · doi:10.1371/journal.pgen.0010008 · Cited by 443

Telomerase modulates expression of growth-controlling genes and enhances cell proliferation

Smith, L. L., Coller, H. A., & Roberts, J. M. (2003) · Nature Cell Biology · doi:10.1038/ncb985 · Cited by 438

MyD88-mediated signaling prevents development of adenocarcinomas of the colon: Role of interleukin 18

Salcedo, R., Worschech, A., Cardone, M., Jones, Y., Gyulai, Z., Dai, R.-M., Wang, E., Ma, W., Haines, D., O'hUigin, C., et al. (2010) · Journal of Experimental Medicine · doi:10.1084/jem.20100199 · Cited by 429

AGEMAP: A Gene Expression Database for Aging in Mice

Zahn, J. M., Poosala, S., Owen, A. B., Ingram, D. K., Lustig, A., Carter, A., Weeraratna, A. T., Taub, D. D., Gorospe, M., Mazan-Mamczarz, K., et al. (2007) · PLoS Genetics · doi:10.1371/journal.pgen.0030201 · Cited by 431

Systematic survey reveals general applicability of "guilt-by-association" within gene coexpression networks

Wolfe, C. J., Kohane, I. S., & Butte, A. J. (2005) · BMC Bioinformatics · doi:10.1186/1471-2105-6-227 · Cited by 422

Concordant Regulation of Translation and mRNA Abundance for Hundreds of Targets of a Human microRNA

Hendrickson, D. G., Hogan, D. J., McCullough, H. L., Myers, J. W., Herschlag, D., Ferrell, J. E., & Brown, P. O. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000238 · Cited by 418

UV Signature Mutations

Brash, D. E. (2015) · Photochemistry and Photobiology · doi:10.1111/php.12377 · Cited by 401

Intracellular crowding defines the mode and sequence of substrate uptake by Escherichia coli and constrains its metabolic activity

Beg, Q. K., Vazquez, A., Ernst, J., de Menezes, M. A., Bar-Joseph, Z., Barabási, A.-L., & Oltvai, Z. N. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0609845104 · Cited by 368

Nucleus alignment and cell signaling in fibroblasts: response to a micro-grooved topography

Dalby, M. J., Riehle, M. O., Yarwood, S. J., Wilkinson, C. D. W., & Curtis, A. S. G. (2003) · Experimental Cell Research · doi:10.1016/s0014-4827(02)00053-8 · Cited by 408

Genome-wide Analysis of Gene Expression Regulated by the Calcineurin/Crz1p Signaling Pathway in Saccharomyces cerevisiae

Yoshimoto, H., Saltsman, K., Gasch, A. P., Li, H. X., Ogawa, N., Botstein, D., Brown, P. O., & Cyert, M. S. (2002) · Journal of Biological Chemistry · doi:10.1074/jbc.m202718200 · Cited by 404

Proteomic Analysis of Integrin-Associated Complexes Identifies RCC2 as a Dual Regulator of Rac1 and Arf6

Humphries, J. D., Byron, A., Bass, M. D., Craig, S. E., Pinney, J. W., Knight, D., & Humphries, M. J. (2009) · Science Signaling · doi:10.1126/scisignal.2000396 · Cited by 404

Molecular classification and prognostication of adrenocortical tumors by transcriptome profiling

Giordano, T. J., Kuick, R., Else, T., Gauger, P. G., Vinco, M., Bauersfeld, J., Sanders, D., Thomas, D. G., Doherty, G., & Hammer, G. (2009) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-08-1067 · Cited by 401

Dissecting the Unique Role of the Retinoblastoma Tumor Suppressor during Cellular Senescence

Chicas, A., Wang, X., Zhang, C., McCurrach, M., Zhao, Z., Mert, O., Dickins, R. A., Narita, M., Zhang, M., & Lowe, S. W. (2010) · Cancer Cell · doi:10.1016/j.ccr.2010.01.023 · Cited by 388

Identification of eukaryotic mRNAs that are translated at reduced cap binding complex eIF4F concentrations using a cDNA microarray

Johannes, G., Carter, M. S., Eisen, M. B., Brown, P. O., & Sarnow, P. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.23.13118 · Cited by 394

A Pilot Study of Circulating miRNAs as Potential Biomarkers of Early Stage Breast Cancer

Zhao, H., Shen, J., Medico, L., Wang, D., Ambrosone, C. B., & Liu, S. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013735 · Cited by 398

Replication and refinement of a vaginal microbial signature of preterm birth in two racially distinct cohorts of US women

Callahan, B. J., DiGiulio, D. B., Goltsman, D. S. A., Sun, C. L., Costello, E. K., Jeganathan, P., Biggio, J. R., Wong, R. J., Druzin, M. L., Shaw, G. M., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1705899114 · Cited by 391

Automatic speech emotion recognition using modulation spectral features

Wu, S., Falk, T. H., & Chan, W.-Y. (2011) · Speech Communication · doi:10.1016/j.specom.2010.08.013 · Cited by 389

Genome-wide responses to mitochondrial dysfunction

Epstein, C. B., Waddle, J. A., Hale, W., Davé, V., Thornton, J., Macatee, T. L., Garner, H. R., & Butow, R. A. (2001) · Molecular Biology of the Cell · doi:10.1091/mbc.12.2.297 · Cited by 389

Synthetic lethal interaction of combined BCL-XL and MEK inhibition promotes tumor regressions in KRAS mutant cancer models

Corcoran, R. B., Cheng, K. A., Hata, A. N., Faber, A. C., Ebi, H., Coffee, E. M., Greninger, P., Brown, R. D., Godfrey, J. T., Cohoon, T. J., et al. (2013) · Cancer Cell · doi:10.1016/j.ccr.2012.11.007 · Cited by 377

The expression of adipogenic genes is decreased in obesity and diabetes mellitus

Nadler, S. T., Stoehr, J. P., Schueler, K. L., Tanimoto, G., Yandell, B. S., & Attie, A. D. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.21.11371 · Cited by 386

Distinct transcriptional profiles of adrenocortical tumors uncovered by DNA microarray analysis

Giordano, T. J., Thomas, D. G., Kuick, R., Lizyness, M., Misek, D. E., Smith, A. L., Sanders, D., Aljundi, R. T., Gauger, P. G., Thompson, N. W., et al. (2003) · The American Journal of Pathology · doi:10.1016/s0002-9440(10)63846-1 · Cited by 383

Gene expression analysis identifies global gene dosage sensitivity in cancer

Fehrmann, R. S. N., Karjalainen, J. M., Krajewska, M., Westra, H.-J., Maloney, D., Simeonov, A., Pers, T. H., Hirschhorn, J. N., Jansen, R. C., Schultes, E. A., et al. (2015) · Nature Genetics · doi:10.1038/ng.3173 · Cited by 347

Transcription Profiling of Candida albicans Cells Undergoing the Yeast-to-Hyphal Transition

Nantel, A., Dignard, D., Bachewich, C., Harcus, D., Marcil, A., Bouin, A.-P., Sensen, C. W., Hogues, H., van het Hoog, M., Gordon, P., et al. (2002) · Molecular Biology of the Cell · doi:10.1091/mbc.e02-05-0272 · Cited by 378

MDA-MB-435 cells are derived from M14 Melanoma cells––a loss for breast cancer, but a boon for melanoma research

Rae, J. M., Creighton, C. J., Meck, J. M., Haddad, B. R., & Johnson, M. D. (2007) · Breast Cancer Research and Treatment · doi:10.1007/s10549-006-9392-8 · Cited by 374

A Systematic Mammalian Genetic Interaction Map Reveals Pathways Underlying Ricin Susceptibility

Bassik, M. C., Kampmann, M., Lebbink, R. J., Wang, S., Hein, M. Y., Poser, I., Weibezahn, J., Horlbeck, M. A., Chen, S., Mann, M., et al. (2013) · Cell · doi:10.1016/j.cell.2013.01.030 · Cited by 365

The Fungal Pathogen Candida albicans Autoinduces Hyphal Morphogenesis by Raising Extracellular pH

Vylkova, S., Carman, A. J., Danhof, H. A., Collette, J. R., Zhou, H., & Lorenz, M. C. (2011) · mBio · doi:10.1128/mbio.00055-11 · Cited by 365

IGF-I induced genes in stromal fibroblasts predict the clinical outcome of breast and lung cancer patients

Rajski, M., Zanetti-Dällenbach, R., Vogel, B., Herrmann, R., Rochlitz, C., & Buess, M. (2010) · BMC Medicine · doi:10.1186/1741-7015-8-1 · Cited by 355

Transcriptional profiling of aging in human muscle reveals a common aging signature

Zahn, J. M., Sonu, R., Vogel, H., Crane, E., Mazan-Mamczarz, K., Rabkin, R., Davis, R. W., Becker, K. G., Owen, A. B., & Kim, S. K. (2006) · PLoS Genetics · doi:10.1371/journal.pgen.0020115 · Cited by 351

Integrating regulatory motif discovery and genome-wide expression analysis

Conlon, E. M., Liu, X. S., Lieb, J. D., & Liu, J. S. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0630591100 · Cited by 343

The Global Transcriptional Response to Transient Cell Wall Damage in Saccharomyces cerevisiae and Its Regulation by the Cell Integrity Signaling Pathway

García, R., Bermejo, C., Grau, C., Pérez, R., Rodríguez-Peña, J. M., Francois, J., Nombela, C., & Arroyo, J. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m312954200 · Cited by 338

Regulatory Networks Revealed by Transcriptional Profiling of Damaged Saccharomyces cerevisiae Cells: Rpn4 Links Base Excision Repair with Proteasomes

Jelinsky, S. A., Estep, P., Church, G. M., & Samson, L. D. (2000) · Molecular and Cellular Biology · doi:10.1128/mcb.20.21.8157-8167.2000 · Cited by 335

Bone marrow mesenchymal stem cells are abnormal in multiple myeloma

Corre, J., Mahtouk, K., Attal, M., Gadelorge, M., Huynh, A., Fleury-Cappellesso, S., Danho, C., Laharrague, P., Klein, B., Rème, T., et al. (2007) · Leukemia · doi:10.1038/sj.leu.2404621 · Cited by 328

Comparative Metabolic Flux Profiling of Melanoma Cell Lines

Scott, D. A., Richardson, A. D., Filipp, F. V., Knutzen, C. A., Chiang, G. G., Ronai, Z. A., Osterman, A. L., & Smith, J. W. (2011) · Journal of Biological Chemistry · doi:10.1074/jbc.m111.282046 · Cited by 328

Expression differences for genes involved in lignin, glutathione and sulphate metabolism in response to cadmium in Arabidopsis thaliana and the related Zn/Cd‐hyperaccumulator Thlaspi caerulescens

VAN DE MORTEL, J. E., SCHAT, H., MOERLAND, P. D., VAN THEMAAT, E. V. L., VAN DER ENT, S., BLANKESTIJN, H., GHANDILYAN, A., TSIATSIANI, S., & AARTS, M. G. M. (2008) · Plant, Cell & Environment · doi:10.1111/j.1365-3040.2007.01764.x · Cited by 326

Stress-activated Genomic Expression Changes Serve a Preparative Role for Impending Stress in Yeast

Berry, D. B., & Gasch, A. P. (2008) · Molecular Biology of the Cell · doi:10.1091/mbc.e07-07-0680 · Cited by 326

Comprehensive curation and analysis of global interaction networks in Saccharomyces cerevisiae

Reguly, T., Breitkreutz, A., Boucher, L., Breitkreutz, B.-J., Hon, G. C., Myers, C. L., Parsons, A., Friesen, H., Oughtred, R., Tong, A., et al. (2006) · Journal of Biology · doi:10.1186/jbiol36 · Cited by 326

miRNA–target chimeras reveal miRNA 3′-end pairing as a major determinant of Argonaute target specificity

Moore, M. J., Scheel, T. K. H., Luna, J. M., Park, C. Y., Fak, J. J., Nishiuchi, E., Rice, C. M., & Darnell, R. B. (2015) · Nature Communications · doi:10.1038/ncomms9864 · Cited by 326

When is hub gene selection better than standard meta-analysis?

Langfelder, P., Mischel, P. S., & Horvath, S. (2013) · PLoS ONE · doi:10.1371/journal.pone.0061505 · Cited by 313

Subtypes of Preeclampsia: Recognition and Determining Clinical Usefulness

Roberts, J. M., Rich-Edwards, J. W., McElrath, T. F., Garmire, L., Myatt, L., & for the Global Pregnancy Collaboration (2021) · Hypertension · doi:10.1161/hypertensionaha.120.14781 · Cited by 311

Auxin-related gene families in abiotic stress response in Sorghum bicolor

Wang, S., Bai, Y., Shen, C., Wu, Y., Zhang, S., Jiang, D., Guilfoyle, T. J., Chen, M., & Qi, Y. (2010) · Functional & Integrative Genomics · doi:10.1007/s10142-010-0174-3 · Cited by 297

Diverse and Specific Gene Expression Responses to Stresses in Cultured Human Cells

Murray, J. I., Whitfield, M. L., Trinklein, N. D., Myers, R. M., Brown, P. O., & Botstein, D. (2004) · Molecular Biology of the Cell · doi:10.1091/mbc.e03-11-0799 · Cited by 300

PTEN negatively regulates neural stem cell self-renewal by modulating G 0 -G 1 cell cycle entry

Groszer, M., Erickson, R., Scripture-Adams, D. D., Dougherty, J. D., Le Belle, J., Zack, J. A., Geschwind, D. H., Liu, X., Kornblum, H. I., & Wu, H. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0509939103 · Cited by 306

Treatment for 2 mo with n 3 polyunsaturated fatty acids reduces adiposity and some atherogenic factors but does not improve insulin sensitivity in women with type 2 diabetes: A randomized controlled study

Kabir, M., Skurnik, G., Naour, N., Pechtner, V., Meugnier, E., Rome, S., Quignard-Boulangé, A., Vidal, H., Slama, G., Clément, K., et al. (2007) · The American Journal of Clinical Nutrition · doi:10.1093/ajcn/86.5.1670 · Cited by 316

Suppression of myeloid transcription factors and induction of STAT response genes by AML-specific Flt3 mutations

Mizuki, M., Schwäble, J., Steur, C., Choudhary, C., Agrawal, S., Sargin, B., Steffen, B., Matsumura, I., Kanakura, Y., Böhmer, F. D., et al. (2003) · Blood · doi:10.1182/blood-2002-06-1677 · Cited by 298

Early-branching gut fungi possess a large, comprehensive array of biomass-degrading enzymes

Solomon, K. V., Haitjema, C. H., Henske, J. K., Gilmore, S. P., Borges-Rivera, D., Lipzen, A., Brewer, H. M., Purvine, S. O., Wright, A. T., Theodorou, M. K., et al. (2016) · Science · doi:10.1126/science.aad1431 · Cited by 302

Longitudinal Study of Postconcussion Syndrome: Not Everyone Recovers

Hiploylee, C., Dufort, P. A., Davis, H. S., Wennberg, R. A., Tartaglia, M. C., Mikulis, D., Hazrati, L.-N., & Tator, C. H. (2017) · Journal of Neurotrauma · doi:10.1089/neu.2016.4677 · Cited by 293

Evidence accumulation and the moment of recognition: dissociating perceptual recognition processes using fMRI

Ploran, E. J., Nelson, S. M., Velanova, K., Donaldson, D. I., Petersen, S. E., & Wheeler, M. E. (2007) · The Journal of Neuroscience · doi:10.1523/jneurosci.3522-07.2007 · Cited by 282

Lipoprotein lipase links dietary fat to solid tumor cell proliferation

Kuemmerle, N. B., Rysman, E., Lombardo, P. S., Flanagan, A. J., Lipe, B. C., Wells, W. A., Pettus, J. R., Froehlich, H. M., Memoli, V. A., Morganelli, P. M., et al. (2011) · Molecular Cancer Therapeutics · doi:10.1158/1535-7163.mct-10-0802 · Cited by 286

Peripheral blood mononuclear cell gene expression profiles identify emergent post-traumatic stress disorder among trauma survivors

Segman, R. H., Shefi, N., Goltser-Dubner, T., Friedman, N., Kaminski, N., & Shalev, A. Y. (2005) · Molecular Psychiatry · doi:10.1038/sj.mp.4001636 · Cited by 281

Large-Scale Genetic Perturbations Reveal Regulatory Networks and an Abundance of Gene-Specific Repressors

Kemmeren, P., Sameith, K., van de Pasch, L. A. L., Benschop, J. J., Lenstra, T. L., Margaritis, T., O’Duibhir, E., Apweiler, E., van Wageningen, S., Ko, C. W., et al. (2014) · Cell · doi:10.1016/j.cell.2014.02.054 · Cited by 277

Cell-Type-Based Analysis of MicroRNA Profiles in the Mouse Brain

He, M., Liu, Y., Wang, X., Zhang, M. Q., Hannon, G. J., & Huang, Z. J. (2012) · Neuron · doi:10.1016/j.neuron.2011.11.010 · Cited by 277

DREAM4: combining genetic and dynamic information to identify biological networks and dynamical models

Greenfield, A., Madar, A., Ostrer, H., & Bonneau, R. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013397 · Cited by 255

Systematic changes in gene expression in postmortem human brains associated with tissue pH and terminal medical conditions

Li, J. Z., Vawter, M. P., Walsh, D. M., Tomita, H., Evans, S. J., Choudary, P. V., Lopez, J. F., Avelar, A., Shokoohi, V., Chung, T., et al. (2004) · Human Molecular Genetics · doi:10.1093/hmg/ddh065 · Cited by 261

eSGA: E. coli synthetic genetic array analysis

Butland, G., Babu, M., Díaz-Mejía, J. J., Bohdana, F., Phanse, S., Gold, B., Yang, W., Li, J., Gagarinova, A. G., Pogoutse, O., et al. (2008) · Nature Methods · doi:10.1038/nmeth.1239 · Cited by 256

Gene expression profiling of human adrenocortical tumors using complementary deoxyribonucleic acid microarrays identifies several candidate genes as markers of malignancy

de Fraipont, F., El Atifi, M., Cherradi, N., Le Moigne, G., Defaye, G., Houlgatte, R., Bertherat, J., Bertagna, X., Plouin, P.-F., Baudin, E., et al. (2005) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2004-1075 · Cited by 261

Time- and exercise-dependent gene regulation in human skeletal muscle

Zambon, A. C., McDearmon, E. L., Salomonis, N., Vranizan, K. M., Johansen, K. L., Adey, D., Takahashi, J. S., Schambelan, M., & Conklin, B. R. (2003) · Genome Biology · doi:10.1186/gb-2003-4-10-r61 · Cited by 254

The chaplins: a family of hydrophobic cell-surface proteins involved in aerial mycelium formation in Streptomyces coelicolor

Elliot, M. A., Karoonuthaisiri, N., Huang, J., Bibb, M. J., Cohen, S. N., Kao, C. M., & Buttner, M. J. (2003) · Genes & Development · doi:10.1101/gad.264403 · Cited by 246

Reproducibility of CT Radiomic Features within the Same Patient: Influence of Radiation Dose and CT Reconstruction Settings

Meyer, M., Ronald, J., Vernuccio, F., Nelson, R. C., Ramirez-Giraldo, J. C., Solomon, J., Patel, B. N., Samei, E., & Marin, D. (2019) · Radiology · doi:10.1148/radiol.2019190928 · Cited by 258

Genome-wide Analysis of the Response to Cell Wall Mutations in the Yeast Saccharomyces cerevisiae

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The exposure of autoantigens by microparticles underlies the formation of potent inflammatory components: the microparticle‐associated immune complexes

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