limma: Linear Models for Microarray Data

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

Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments

Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829

Variance stabilization applied to microarray data calibration and to the quantification of differential expression

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Identifying differentially expressed genes using false discovery rate controlling procedures

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Use of within-array replicate spots for assessing differential expression in microarray experiments

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Analysis of Messy Data, Volume I: Designed Experiments

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Statistical Issues in cDNA Microarray Data Analysis

Smyth, G. K., Yang, J. Y. H., & Speed, T. P. (2003) · Humana Press eBooks · doi:10.1385/1-59259-364-x:111 · Cited by 471

Parameter estimation for the calibration and variance stabilization of microarray data

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Design and analysis of comparative microarray experiments

Speed, T. P. (2003) · doi:10.1201/9780203011232-9 · Cited by 67

Seasonal Differences of Gene Expression Profiles in Song Sparrow (Melospiza melodia) Hypothalamus in Relation to Territorial Aggression

Mukai, M., Replogle, K. L., Drnevich, J. M., Wang, G., Wacker, D. W., Band, M., Clayton, D. F., & Wingfield, J. C. (2009) · PLoS ONE · doi:10.1371/journal.pone.0008182 · Cited by 84

DNA Methylation Signature of Childhood Chronic Physical Aggression in T Cells of Both Men and Women

Guillemin, C., Provençal, N., Suderman, M. J., Côté, S. M., Vitaro, F., Hallett, M. T., Tremblay, R. E., & Szyf, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0086822 · Cited by 84

Systematic Analysis and Biomarker Study for Alzheimer’s Disease

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Meta‐analysis of genome‐wide DNA methylation and integrative omics of age in human skeletal muscle

Voisin, S. A. C., Jacques, M., Landen, S., Harvey, N. R., Haupt, L. M., Griffiths, L. R., Gancheva, S., Ouni, M., Jähnert, M., Ashton, K. J., et al. (2021) · Journal of Cachexia Sarcopenia and Muscle · doi:10.1002/jcsm.12741 · Cited by 93

Defective cytokinin signaling reprograms lipid and flavonoid gene-to-metabolite networks to mitigate high salinity in Arabidopsis

Abdelrahman, M., Nishiyama, R., Tran, C. D., Kusano, M., Nakabayashi, R., Okazaki, Y., Matsuda, F., Montes, R. A. C., Mostofa, M. G., Li, W., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2105021118 · Cited by 84

Alteration in 5-hydroxymethylcytosine-mediated epigenetic regulation leads to Purkinje cell vulnerability in ATM deficiency

Jiang, D., Zhang, Y., Hart, R. P., Chen, J., Herrup, K., & Li, J. (2015) · Brain · doi:10.1093/brain/awv284 · Cited by 84

Transcriptome Analysis of Wnt3a-Treated Triple-Negative Breast Cancer Cells

Maubant, S., Tesson, B. M., Maire, V., Ye, M., Rigaill, G. J., Gentien, D., Cruzalegui, F. H., Tucker, G. C., Roman‐Roman, S., & Dubois, T. (2015) · PLoS ONE · doi:10.1371/journal.pone.0122333 · Cited by 85

Gene expression shifts during perithecium development in Gibberella zeae (anamorph Fusarium graminearum), with particular emphasis on ion transport proteins

Hallen‐Adams, H. E., Huebner, M., Shiu, S., Güldener, U., & Trail, F. (2007) · Fungal Genetics and Biology · doi:10.1016/j.fgb.2007.04.007 · Cited by 84

Tissue-Specific Molecular Biomarker Signatures of Type 2 Diabetes: An Integrative Analysis of Transcriptomics and Protein–Protein Interaction Data

Turanlı, B., Karagoz, K., Sevimoğlu, T., Kılıç, E., Göv, E., & Arğa, K. Y. (2015) · OMICS A Journal of Integrative Biology · doi:10.1089/omi.2015.0088 · Cited by 87

Mapping Genetic Contributions to Cardiac Pathology Induced by Beta-Adrenergic Stimulation in Mice

Rau, C. D., Wang, J., Avetisyan, R., Romay, M. C., Martin, L., Ren, S. V., Wang, Y., & Lusis, A. J. (2014) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.113.000732 · Cited by 84

Analysis of the Cerebrospinal Fluid Proteome in Alzheimer's Disease

Khoonsari, P. E., Månberg, A., Lönnberg, M., Mikus, M. S., Kilander, L., Lannfelt, L., Bergquist, J., Ingelsson, M., Nilsson, P., Kultima, K., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0150672 · Cited by 86

Gene expression profiling of 1200 pancreatic ductal adenocarcinoma reveals novel subtypes

Zhao, L., Zhao, H., & Yan, H. (2018) · BMC Cancer · doi:10.1186/s12885-018-4546-8 · Cited by 93

COL5A1 may contribute the metastasis of lung adenocarcinoma

Liu, W., Wei, H., Gao, Z., Chen, G., Liu, Y., Gao, X., Bai, G., He, S., Liu, T., Xu, W., et al. (2018) · Gene · doi:10.1016/j.gene.2018.04.066 · Cited by 83

Rootstock-regulated gene expression patterns in apple tree scions

Jensen, P. J., Makałowska, I., Altman, N., Fazio, G., Praul, C. A., Maximova, S. N., Crassweller, R. M., Travis, J. W., & McNellis, T. W. (2009) · Tree Genetics & Genomes · doi:10.1007/s11295-009-0228-7 · Cited by 88

REG gene expression in inflamed and healthy colon mucosa explored by in situ hybridisation

Granlund, A. V. B., Østvik, A. E., Brenna, Ø., TORP, S. H., Gustafsson, B. I., & Sandvik, A. K. (2013) · Cell and Tissue Research · doi:10.1007/s00441-013-1592-z · Cited by 86

Integration of transcriptomics and metabolomics data specifies the metabolic response of Chlamydomonas to rapamycin treatment

Kleeßen, S., Irgang, S., Klie, S., Giavalisco, P., & Nikoloski, Z. (2015) · The Plant Journal · doi:10.1111/tpj.12763 · Cited by 83

Placental transcriptome in development and pathology: expression, function, and methods of analysis

Cox, B., Leavey, K., Nosi, U., Wong, F., & Kingdom, J. C. (2015) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2015.07.046 · Cited by 86

Linking mechanistic and behavioral responses to sublethal esfenvalerate exposure in the endangered delta smelt; Hypomesus transpacificus (Fam. Osmeridae)

Connon, R. E., Geist, J. P., Pfeiff, J., Loguinov, A. V., D'Abronzo, L. S., Henri Wintz, A., Vulpe, C. D., & Werner, I. (2009) · BMC Genomics · doi:10.1186/1471-2164-10-608 · Cited by 83

Genetic and Molecular Characterization of Submergence Response Identifies Subtol6 as a Major Submergence Tolerance Locus in Maize

Campbell, M. T., Proctor, C. A., Dou, Y., Schmitz, A. J., Phansak, P., Kruger, G. R., Zhang, C., & Walia, H. (2015) · PLoS ONE · doi:10.1371/journal.pone.0120385 · Cited by 83

Empirical assessment of analysis workflows for differential expression analysis of human samples using RNA-Seq

Williams, C., Baccarella, A., Parrish, J. Z., & Kim, C. C. (2017) · BMC Bioinformatics · doi:10.1186/s12859-016-1457-z · Cited by 83

Inbreeding by Environmental Interactions Affect Gene Expression in Drosophila melanogaster

Kristensen, T. N., Sørensen, P. B., Pedersen, K. S., Kruhøffer, M., & Loeschcke, V. (2006) · Genetics · doi:10.1534/genetics.105.054486 · Cited by 83

Maternal obesity and diabetes induces latent metabolic defects and widespread epigenetic changes in isogenic mice

Li, C. C. Y., Young, P. E., Maloney, C., Eaton, S. A., Cowley, M. J., Buckland, M. E., Preiß, T., Henstridge, D. C., Cooney, G. J., Febbraio, M. A., et al. (2013) · Epigenetics · doi:10.4161/epi.24656 · Cited by 83

Clinically Relevant Post-Translational Modification Analyses—Maturing Workflows and Bioinformatics Tools

Pascovici, D., Wu, J. X., McKay, M. J., Joseph, C., Noor, Z., Kamath, K. S., Wu, Y., Ranganathan, S., Gupta, V., & Mirzaei, M. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms20010016 · Cited by 82

Robustness of differential gene expression analysis of RNA-seq

Stupnikov, A., McInerney, C. E., Savage, K. I., McIntosh, S., Emmert‐Streib, F., Kennedy, R. D., Salto‐Tellez, M., Prise, K. M., & McArt, D. G. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.05.040 · Cited by 84

Molecular Subgroups of Intrahepatic Cholangiocarcinoma Discovered by Single-Cell RNA Sequencing–Assisted Multiomics Analysis

Bao, X., Li, Q., Chen, J., Chen, D., Ye, C., Dai, X., Wang, Y., Li, X., Rong, X., Cheng, F., et al. (2022) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-21-1101 · Cited by 82

Comprehensive Identification of Salmonella enterica Serovar Typhimurium Genes Required for Infection of BALB/c Mice

Chaudhuri, R. R., Peters, S. E., Pleasance, S. J., Northen, H., Willers, C., Paterson, G. K., Cone, D. B., Allen, A. G., Owen, P., Shalom, G., et al. (2009) · PLoS Pathogens · doi:10.1371/journal.ppat.1000529 · Cited by 82

Identification of Differentially Expressed MicroRNA in Parathyroid Tumors

Rahbari, R. M., Holloway, A. K., He, M., Khanafshar, E., Clark, O. H., & Kebebew, E. (2010) · Annals of Surgical Oncology · doi:10.1245/s10434-010-1359-7 · Cited by 82

A complementary role for ELF3 and TFL1 in the regulation of flowering time by ambient temperature

Strasser, B., Alvarez, M. J., Califano, A., & Cerdán, P. D. (2009) · The Plant Journal · doi:10.1111/j.1365-313x.2009.03811.x · Cited by 82

Functional evidence that Drosha overexpression in cervical squamous cell carcinoma affects cell phenotype and microRNA profiles

Muralidhar, B., Winder, D. M., Murray, M. J., Palmer, R. D., Barbosa‐Morais, N. L., Saini, H. K., Roberts, I., Pett, M. R., & Coleman, N. (2011) · The Journal of Pathology · doi:10.1002/path.2898 · Cited by 82

Loss of Osteoclasts Contributes to Development of Osteosarcoma Pulmonary Metastases

Endo‐Munoz, L., Cumming, A., Rickwood, D., Wilson, D., Cueva, C., Ng, C. K. Y., Strutton, G., Cassady, A. I., Evdokiou, A., Sommerville, S. M. M., et al. (2010) · Cancer Research · doi:10.1158/0008-5472.can-09-4291 · Cited by 82

Expression of protocadherin gamma in skeletal muscle tissue is associated with age and muscle weakness

Hangelbroek, R., Fazelzadeh, P., Tieland, M., Boekschoten, M. V., Hooiveld, G. J. E. J., van Duynhoven, J., Timmons, J. A., Verdijk, L. B., de Groot, C. P. G. M., van Loon, L. J. C., et al. (2016) · Journal of Cachexia Sarcopenia and Muscle · doi:10.1002/jcsm.12099 · Cited by 83

A five-gene expression signature to predict progression in T1G3 bladder cancer

van der Heijden, A. G., Mengual, L., Lozano, J. J., Ingelmo‐Torres, M., Ribal, M. J., Fernández, P. L., Oosterwijk, E., Schalken, J. A., Alcaraz, A., & Witjes, J. A. (2016) · European Journal of Cancer · doi:10.1016/j.ejca.2016.06.003 · Cited by 82

DNA methylation signature in peripheral blood reveals distinct characteristics of human X chromosome numerical aberrations

Sharma, A., Jamil, M. A., Nuesgen, N., Schreiner, F., Priebe, L., Hoffmann, P., Herns, S., Nöthen, M. M., Fröhlich, H., Oldenburg, J., et al. (2015) · Clinical Epigenetics · doi:10.1186/s13148-015-0112-2 · Cited by 81

A KRAS variant is a biomarker of poor outcome, platinum chemotherapy resistance and a potential target for therapy in ovarian cancer

Ratner, E., Keane, F. K., Lindner, R. M., Tassi, R. A., Paranjape, T., Glasgow, M. A., Nallur, S. V., Deng, Y., Lu, L., Steele, L., et al. (2011) · Oncogene · doi:10.1038/onc.2011.539 · Cited by 81

Aberrant expression of cell cycle and material metabolism related genes contributes to hepatocellular carcinoma occurrence

Yan, H., Li, Z., Shen, Q., Wang, Q., Tian, J., Jiang, Q., & Gao, L. (2017) · Pathology - Research and Practice · doi:10.1016/j.prp.2017.01.019 · Cited by 81

Obesity-associated inflammation triggers an autophagy–lysosomal response in adipocytes and causes degradation of perilipin 1

Ju, L., Han, J., Zhang, X., Deng, Y., Han, Y., Wang, C., Li, X., Chen, S., Alimujiang, M., Li, X., et al. (2019) · Cell Death and Disease · doi:10.1038/s41419-019-1393-8 · Cited by 81

New barcoded primers for efficient retrieval of cercozoan sequences in high‐throughput environmental diversity surveys, with emphasis on worldwide biological soil crusts

Fiore‐Donno, A. M., Rixen, C., Rippin, M., Glaser, K., Samolov, E., Karsten, U., Becker, B., & Bonkowski, M. (2017) · Molecular Ecology Resources · doi:10.1111/1755-0998.12729 · Cited by 83

ATF7-Dependent Epigenetic Changes Are Required for the Intergenerational Effect of a Paternal Low-Protein Diet

Yoshida, K., Maekawa, T., Ly, N. H., Fujita, S.-I., Muratani, M., Ando, M., Katou, Y., Araki, H., Miura, F., Shirahige, K., et al. (2020) · Molecular Cell · doi:10.1016/j.molcel.2020.02.028 · Cited by 82

Interleukin 17 Promotes Expression of Alarmins S100A8 and S100A9 During the Inflammatory Response of Keratinocytes

Christmann, C., Zenker, S., Martens, L., Hübner, J., Loser, K., Vogl, T., & Roth, J. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2020.599947 · Cited by 81

Placental cell type deconvolution reveals that cell proportions drive preeclampsia gene expression differences

Campbell, K. A., Colacino, J. A., Puttabyatappa, M., Dou, J., Elkin, E. R., Hammoud, S. S., Domino, S. E., Dolinoy, D. C., Goodrich, J. M., Loch-Caruso, R. K., et al. (2023) · Communications Biology · doi:10.1038/s42003-023-04623-6 · Cited by 84

Molecular Mechanisms Mediating Retinal Reactive Gliosis Following Bone Marrow Mesenchymal Stem Cell Transplantation

Tassoni, A., Gutteridge, A., Barber, A. C., Osborne, A., & Martin, K. R. G. (2015) · Stem Cells · doi:10.1002/stem.2095 · Cited by 84

Global comparative transcriptome analysis of cartilage formation in vivo

Cameron, T. L., Belluoccio, D., Farlie, P. G., Brachvogel, B., & Bateman, J. F. (2009) · BMC Developmental Biology · doi:10.1186/1471-213x-9-20 · Cited by 81

Widespread duplications in the genomes of laboratory stocks of Dictyostelium discoideum

Bloomfield, G., Tanaka, Y., Skelton, J., Ivens, A. C., & Kay, R. R. (2008) · Genome biology · doi:10.1186/gb-2008-9-4-r75 · Cited by 84

Proteomics and transcriptomics of the BABA-induced resistance response in potato using a novel functional annotation approach

Bengtsson, T., Weighill, D. A., Proux‐Wéra, E., Levander, F., Resjö, S., Burra, D. D., Moushib, L. I., Hedley, P. E., Liljeroth, E., Jacobson, D. A., et al. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-315 · Cited by 81

Gene expression profiling of acute myeloid leukemia samples from adult patients with AML-M1 and -M2 through boutique microarrays, real-time PCR and droplet digital PCR

Handschuh, L., Kaźmierczak, M., Milewski, M., ralski, M. G. ⁄., Łuczak, M., Wojtaszewska, M. L., Uszczyńska-Ratajczak, B., Lewandowski, K. C., Komarnicki, M. A., & Figlerowicz, M. (2017) · International Journal of Oncology · doi:10.3892/ijo.2017.4233 · Cited by 82

An analysis of gene expression in PTSD implicates genes involved in the glucocorticoid receptor pathway and neural responses to stress

Logue, M. W., Smith, A. K., Baldwin, C., Wolf, E. J., Guffanti, G., Ratanatharathorn, A., Stone, A., Schichman, S. A., Humphries, D., Binder, E. B., et al. (2015) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2015.03.016 · Cited by 80

Differences in gene expression profiles between human preimplantation embryos cultured in two different IVF culture media

Kleijkers, S. H. M., Eijssen, L., Coonen, E., Derhaag, J. G., Mantikou, E., Jonker, M. J., Mastenbroek, S., Repping, S., Evers, J. L. H., Dumoulin, J. C. M., et al. (2015) · Human Reproduction · doi:10.1093/humrep/dev179 · Cited by 84

Comparative Transcriptomic Analysis of Salt Adaptation in Roots of Contrasting Medicago truncatula Genotypes

Zahaf, O., Blanchet, S., Zelicourt, A. D., Alunni, B., Plet, J., Laffont, C., de Lorenzo, L., Imbeaud, S., Ichanté, J.-L., Diet, A., et al. (2012) · Molecular Plant · doi:10.1093/mp/sss009 · Cited by 80

INVEX—a web-based tool for integrative visualization of expression data

Xia, J., Lyle, N. H., Mayer, M. L., Pena, O. M., & Hancock, R. E. W. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt562 · Cited by 80

Clinically Relevant Plasmid-Host Interactions Indicate that Transcriptional and Not Genomic Modifications Ameliorate Fitness Costs of Klebsiella pneumoniae Carbapenemase-Carrying Plasmids

Buckner, M. M. C., Saw, H. T. H., Osagie, R. N., McNally, A., Ricci, V., Wand, M. E., Woodford, N., Ivens, A. C., Webber, M. A., & Piddock, L. J. V. (2018) · mBio · doi:10.1128/mbio.02303-17 · Cited by 80

Cellular stress promotes NOD1/2‐dependent inflammation via the endogenous metabolite sphingosine‐1‐phosphate

Pei, G., Żyła, J., He, L., Moura‐Alves, P., Steinle, H., Saikali, P., Lozza, L., Nieuwenhuizen, N. E., Weiner, J. M., Mollenkopf, H., et al. (2021) · The EMBO Journal · doi:10.15252/embj.2020106272 · Cited by 83

Association between age and the host response in critically ill patients with sepsis

Michels, E. H. A., Butler, J. M., Reijnders, T. D. Y., Cremer, O. L., Scicluna, B. P., Uhel, F., Sengers, H. P., Schultz, M. J., Knight, J. C., van Vught, L. A., et al. (2022) · Critical Care · doi:10.1186/s13054-022-04266-9 · Cited by 80

Effect of rosemary polyphenols on human colon cancer cells: transcriptomic profiling and functional enrichment analysis

Valdés, A., García‐Cañas, V., Rocamora‐Reverte, L., Gómez‐Martínez, Á., Ferragut, J. A., & Cifuentes, A. (2012) · Genes & Nutrition · doi:10.1007/s12263-012-0311-9 · Cited by 80

Processing of Agilent microRNA array data

López‐Romero, P., González, M. A., Callejas, S., Dopazo, A., & Irizarry, R. A. (2010) · BMC Research Notes · doi:10.1186/1756-0500-3-18 · Cited by 80

Inferring microRNA–mRNA causal regulatory relationships from expression data

Le, T. D., Liu, L., Tsykin, A., Goodall, G. J., Liu, B., Sun, B., & Li, J. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt048 · Cited by 81

Epigenetic mechanisms regulate stage differentiation in the minimized protozoan Giardia lamblia

Sonda, S., Morf, L., Bottová, I., Baetschmann, H., Rehrauer, H., Caflisch, A., Hakimi, M., & Hehl, A. B. (2010) · Molecular Microbiology · doi:10.1111/j.1365-2958.2010.07062.x · Cited by 82

Transcription profiling of the chilling requirement for bud break in apples: a putative role for FLC-like genes

Porto, D. D., Bruneau, M., Perini, P., Anzanello, R., Renou, J., dos Santos, H. P., Fialho, F. B., & Revers, L. F. (2015) · Journal of Experimental Botany · doi:10.1093/jxb/erv061 · Cited by 85

Transcriptional effects of CRP* expression in Escherichia coli

Khankal, R., Chin, J. W., Ghosh, D., & Cirino, P. C. (2009) · Journal of Biological Engineering · doi:10.1186/1754-1611-3-13 · Cited by 80

The presence of methylation quantitative trait loci indicates a direct genetic influence on the level of DNA methylation in adipose tissue

Drong, A. W., Nicholson, G., Hedman, Å. K., Meduri, E., Grundberg, E., Small, K. S., Shin, S.-Y., Bell, J. T., Karpe, F., Soranzo, N., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0055923 · Cited by 79

Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity

Zhang, J. D., Berntenis, N., Roth, A., & Ebeling, M. (2014) · The Pharmacogenomics Journal · doi:10.1038/tpj.2013.39 · Cited by 79

Microarrays Reveal Early Transcriptional Events during the Termination of Larval Diapause in Natural Populations of the Mosquito, Wyeomyia smithii

Emerson, K. J., Bradshaw, W. E., & Holzapfel, C. M. (2010) · PLoS ONE · doi:10.1371/journal.pone.0009574 · Cited by 79

Randomized Trial of Glucosamine and Chondroitin Supplementation on Inflammation and Oxidative Stress Biomarkers and Plasma Proteomics Profiles in Healthy Humans

Navarro, S. L., White, E., Kantor, E. D., Zhang, Y., Rho, J.-H., Song, X., Milne, G. L., Lampe, P. D., & Lampe, J. W. (2015) · PLoS ONE · doi:10.1371/journal.pone.0117534 · Cited by 80

The genomic landscape of phaeochromocytoma

Flynn, A., Benn, D. E., Clifton-Bligh, R. J., Robinson, B. G., Trainer, A. H., James, P. A., Hogg, A., Waldeck, K., George, J., Li, J., et al. (2014) · The Journal of Pathology · doi:10.1002/path.4503 · Cited by 81

Ulcerative Colitis-Associated Long Noncoding RNA, BC012900, Regulates Intestinal Epithelial Cell Apoptosis

Wu, F., Huang, Y., Dong, F., & Kwon, J. H. (2016) · Inflammatory Bowel Diseases · doi:10.1097/mib.0000000000000691 · Cited by 79

LncRNA XIST serves as a ceRNA to regulate the expression of ASF1A, BRWD1M, and PFKFB2 in kidney transplant acute kidney injury via sponging hsa-miR-212-3p and hsa-miR-122-5p

Cheng, Q., & Wang, L. (2020) · Cell Cycle · doi:10.1080/15384101.2019.1707454 · Cited by 79

A cis-carotene derived apocarotenoid regulates etioplast and chloroplast development

Cazzonelli, C. I., Hou, X., Alagoz, Y., Rivers, J., Dhami, N., Lee, J., Marri, S., & Pogson, B. J. (2020) · eLife · doi:10.7554/elife.45310 · Cited by 80

Genome-wide blood DNA methylation alterations at regulatory elements and heterochromatic regions in monozygotic twins discordant for obesity and liver fat

Ollikainen, M., Ismail, K., Gervin, K., Kyllönen, A., Hakkarainen, A., Lundbom, J., Järvinen, E., Harris, J. R., Lundbom, N. M. I., Rissanen, A., et al. (2015) · Clinical Epigenetics · doi:10.1186/s13148-015-0073-5 · Cited by 80

T1DBase: update 2011, organization and presentation of large-scale data sets for type 1 diabetes research

Burren, O. S., Adlem, E., Achuthan, P., Christensen, M. B., Coulson, R., & Todd, J. A. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq912 · Cited by 79

The Cultural Divide: Exponential Growth in Classical 2D and Metabolic Equilibrium in 3D Environments

Wrzesinski, K., Rogowska-Wrzesińska, A., Kanlaya, R., Borkowski, K., Schwämmle, V., Dai, J., Joensen, K. E., Wojdyła, K., Carvalho, V. B., & Fey, S. J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0106973 · Cited by 81

Potato, Solanum Tuberosum, Defense Against Colorado Potato Beetle, Leptinotarsa Decemlineata (Say): Microarray Gene Expression Profiling of Potato by Colorado Potato Beetle Regurgitant Treatment of Wounded Leaves

Lawrence, S. D., Novak, N. G., Ju, C. J. ‐., & Cooke, J. E. K. (2008) · Journal of Chemical Ecology · doi:10.1007/s10886-008-9507-2 · Cited by 79

Immunogenic males: a genome‐wide analysis of reproduction and the cost of mating in Drosophila melanogaster females

Innocenti, P., & Morrow, E. H. (2009) · Journal of Evolutionary Biology · doi:10.1111/j.1420-9101.2009.01708.x · Cited by 79

Transcriptomic and Phenotypic Analyses Suggest a Network between the Transcriptional Regulators HrcA and σBinListeria monocytogenes

Hu, Y., Oliver, H. F., Raengpradub, S., Palmer, M. E., Orsi, R. H., Wiedmann, M., & Boor, K. J. (2007) · Applied and Environmental Microbiology · doi:10.1128/aem.01281-07 · Cited by 79

The Arabidopsis Mediator Complex Subunit16 Is a Key Component of Basal Resistance against the Necrotrophic Fungal Pathogen Sclerotinia sclerotiorum

Wang, C., Yao, J., Du, X., Zhang, Y., Sun, Y., Rollins, J. A., & Mou, Z. (2015) · PLANT PHYSIOLOGY · doi:10.1104/pp.15.00351 · Cited by 82

Adaptation to heat stress reduces phenotypic and transcriptional plasticity in a marine copepod

Kelly, M. W., Pankey, M. S., DeBiasse, M. B., & Plachetzki, D. C. (2016) · Functional Ecology · doi:10.1111/1365-2435.12725 · Cited by 81

Molecular Signatures in Arabidopsis thaliana in Response to Insect Attack and Bacterial Infection

Barah, P., Winge, P., Kuśnierczyk, A., Tran, D. H., & Bones, A. M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0058987 · Cited by 78

Defective Regulation of MicroRNA Target Genes in Myoblasts from Facioscapulohumeral Dystrophy Patients

Dmitriev, P., Stankevicins, L., Ansseau, E., Petrov, A., Barat, A., Dessen, P., Robert, T., Turki, A., Lazar, V., Labourer, E., et al. (2013) · Journal of Biological Chemistry · doi:10.1074/jbc.m113.504522 · Cited by 79

Analysis of the miRNA–mRNA–lncRNA network in human estrogen receptor-positive and estrogen receptor-negative breast cancer based on TCGA data

Xiao, B., Zhang, W., Chen, L., Hang, J., Wang, L., Zhang, R., Liao, Y., Chen, J., Ma, Q., Sun, Z., et al. (2018) · Gene · doi:10.1016/j.gene.2018.03.011 · Cited by 78

Weighted Gene Co-expression Network Analysis of Endometriosis and Identification of Functional Modules Associated With Its Main Hallmarks

Bakhtiarizadeh, M. R., Hosseinpour, B., Shahhoseini, M., Korte, A., & Gifani, P. (2018) · Frontiers in Genetics · doi:10.3389/fgene.2018.00453 · Cited by 78

Loss of photoreceptorness and gain of genomic alterations in retinoblastoma reveal tumor progression

Kooi, I. E., Mol, B. M., Moll, A. C., van der Valk, P., de Jong, M. C., de Graaf, P., van Mil, S. E., Meeteren, A. Y. N. S., Meijers-Heijboer, H. E. J., Kaspers, G. J. L., et al. (2015) · EBioMedicine · doi:10.1016/j.ebiom.2015.06.022 · Cited by 78

Virulence Evolution of the Human Pathogen Neisseria meningitidis by Recombination in the Core and Accessory Genome

Joseph, B., Schwarz, R. F., Linke, B., Blom, J., Becker, A., Claus, H., Goesmann, A., Frosch, M., Müller, T., Vogel, U. F., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0018441 · Cited by 79

Cross-Species Comparison of Human and Mouse Intestinal Polyps Reveals Conserved Mechanisms in Adenomatous Polyposis Coli (APC)-Driven Tumorigenesis

Gaspar, C., Cardoso, J., Franken, P., Molenaar, L., Morreau, H. M., Möslein, G., Sampson, J. R., Boer, J. M., de Menezes, R. X., & Fodde, R. (2008) · American Journal Of Pathology · doi:10.2353/ajpath.2008.070851 · Cited by 80

Constitutively Elevated Salicylic Acid Levels Alter Photosynthesis and Oxidative State but Not Growth in Transgenic Populus

Xue, L., Guo, W., Yuan, Y., Anino, E. O., Nyamdari, B., Wilson, M. C., Frost, C. J., Chen, H., Babst, B. A., Harding, S. A., et al. (2013) · The Plant Cell · doi:10.1105/tpc.113.112839 · Cited by 78

Iron Deprivation inSynechocystis: Inference of Pathways, Non-coding RNAs, and Regulatory Elements from Comprehensive Expression Profiling

Hernández‐Prieto, M. A., Schön, V., Georg, J., Barreira, L. A., Varela, J. C. S., Hess, W. R., & Futschik, M. E. (2012) · G3 Genes Genomes Genetics · doi:10.1534/g3.112.003863 · Cited by 78

Comparison of small n statistical tests of differential expression applied to microarrays

Murie, C., Woody, O. Z., Lee, A. Y., & Nadon, R. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-45 · Cited by 84

Novel proteins associated with risk for coronary heart disease or stroke among postmenopausal women identified by in-depth plasma proteome profiling

Prentice, R. L., Paczesny, S., Aragaki, A. K., Amon, L. M., Chen, L., Pitteri, S. J., McIntosh, M. W., Wang, P., Busald, T., Hsia, J. A., et al. (2010) · Genome Medicine · doi:10.1186/gm169 · Cited by 78

Layer 2/3 pyramidal cells in the medial prefrontal cortex moderate stress induced depressive behaviors

Shrestha, P., Mousa, A., & Heintz, N. (2015) · eLife · doi:10.7554/elife.08752 · Cited by 84

RNA Enrichment Method for Quantitative Transcriptional Analysis of Pathogens In Vivo Applied to the Fungus Candida albicans

Amorim-Vaz, S., Tran, V. D. T., Pradervand, S., Pagni, M., Coste, A. T., & Sanglard, D. (2015) · mBio · doi:10.1128/mbio.00942-15 · Cited by 81

Metabolome-Wide Association Study of Primary Open Angle Glaucoma

Burgess, L. G., Uppal, K., Walker, D. I., Roberson, R. M., Tran, V., Parks, M. B., Wade, E. A., May, A. T., Umfress, A. C., Jarrell, K. L., et al. (2015) · Investigative Ophthalmology & Visual Science · doi:10.1167/iovs.15-16702 · Cited by 78

A novel function for FOXP3 in humans: intrinsic regulation of conventional T cells

McMurchy, A. N., Gillies, J., Gizzi, M. C., Riba, M., Garcia-Manteiga, J. M., Cittaro, D., Lazarevic, D., Di Nunzio, S., Piras, I. S., Bulfone, A., et al. (2013) · Blood · doi:10.1182/blood-2012-05-431023 · Cited by 77

Changes in Eutopic Endometrial Gene Expression During the Progression of Experimental Endometriosis in the Baboon, Papio Anubis1

Afshar, Y., Hastings, J., Roqueiro, D., Jeong, J.-W., Giudice, L. C., & Fazleabas, A. T. (2013) · Biology of Reproduction · doi:10.1095/biolreprod.112.104497 · Cited by 77

Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice

Bottomly, D., Ferris, M. T., Aicher, L. D., Rosenzweig, E., Whitmore, A. C., Aylor, D. L., Haagmans, B. L., Gralinski, L. E., Bradel-Tretheway, B., Bryan, J. T., et al. (2012) · G3 Genes Genomes Genetics · doi:10.1534/g3.111.001800 · Cited by 78

DNA replication stress differentially regulates G1/S genes via Rad53‐dependent inactivation of Nrm1

Travesa, A., Kuo, D., de Bruin, R. A. M., Kalashnikova, T. I., Guaderrama, M., Thai, K. E., Aslanian, A., Smolka, M. B., Yates, J. R., Ideker, T., et al. (2012) · The EMBO Journal · doi:10.1038/emboj.2012.28 · Cited by 79

ProTargetMiner as a proteome signature library of anticancer molecules for functional discovery

Saei, A. A., Beusch, C. M., Chernobrovkin, A. L., Sabatier, P., Zhang, B., Güler, Ü., Stergiou, E., Gaetani, M., Végvári, Á., & Zubarev, R. A. (2019) · Nature Communications · doi:10.1038/s41467-019-13582-8 · Cited by 77

Network-based identification genetic effect of SARS-CoV-2 infections to Idiopathic pulmonary fibrosis (IPF) patients

Taz, T. A., Ahmed, K., Paul, B. K., Kawsar, M., Aktar, N., Mahmud, S. M. H., & Moni, M. A. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa235 · Cited by 77

sccomp: Robust differential composition and variability analysis for single-cell data

Mangiola, S., Roth‐Schulze, A. J., Trussart, M., Zozaya‐Valdés, E., Ma, M., Gao, Z., Rubin, A. F., Speed, T. P., Shim, H., & Papenfuss, A. T. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2203828120 · Cited by 85

Long‐term adaptation of global transcription and metabolism in the liver of high‐fat diet‐fed C57BL/6J mice

Do, G., Oh, H. Y., Kwon, E., Cho, Y., Shin, S., Park, H., Jeon, S.-M., Kim, E., Hur, C., Park, T., et al. (2011) · Molecular Nutrition & Food Research · doi:10.1002/mnfr.201100064 · Cited by 77

Patient-oriented gene set analysis for cancer mutation data

Boca, S. M., Kinzler, K. W., Velculescu, V. E., Vogelstein, B., & Parmigiani, G. (2010) · Genome biology · doi:10.1186/gb-2010-11-11-r112 · Cited by 77

Co-inhibition of Plasmodium falciparum S-Adenosylmethionine Decarboxylase/Ornithine Decarboxylase Reveals Perturbation-specific Compensatory Mechanisms by Transcriptome, Proteome, and Metabolome Analyses

van Brummelen, A. C., Olszewski, K. L., Wilinski, D., Llinás, M., Louw, A. I., & Birkholtz, L. (2008) · Journal of Biological Chemistry · doi:10.1074/jbc.m807085200 · Cited by 79

Transcriptional response of the photoheterotrophic marine bacterium Dinoroseobacter shibae to changing light regimes

Tomasch, J., Gohl, R., Bunk, B., Diez, M. S., & Wagner‐Döbler, I. (2011) · The ISME Journal · doi:10.1038/ismej.2011.68 · Cited by 77

Signaling pathway activation drift during aging: Hutchinson-Gilford Progeria Syndrome fibroblasts are comparable to normal middle-age and old-age cells

Aliper, A. M., Csoka, A. B., Buzdin, A. A., Jetka, T., Roumiantsev, S. A., Moskalev, A., & Zhavoronkov, A. A. (2015) · Aging · doi:10.18632/aging.100717 · Cited by 79

Limma: linear models for microarray data. In Bioinformatics and computational biology solutions using R and Bioconductor

Smyth, G. K. (2013)

limmaGUI: A graphical user interface for linear modeling of microarray data

Wettenhall, J. M., & Smyth, G. K. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth449 · Cited by 720

Empirical array quality weights in the analysis of microarray data

Ritchie, M. E., Diyagama, D., Neilson, J., van Laar, R., Dobrovic, A., Holloway, A., & Smyth, G. K. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-261 · Cited by 312

Examples

Yes, L. (2010)

LLAMA: AN ONLINE MICROARRAY LINEAR ANALYSIS TOOLPreprint

Routley, B. S., & Muldoon, M. R. (2005) · MIMS EPrints (University of Southampton)