limma: Linear Models for Microarray Data

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

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Identifying differentially expressed genes using false discovery rate controlling procedures

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Parameter estimation for the calibration and variance stabilization of microarray data

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Design and analysis of comparative microarray experiments

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Plasma Metabolomics in Human Pulmonary Tuberculosis Disease: A Pilot Study

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miR-10b-5p expression in Huntington’s disease brain relates to age of onset and the extent of striatal involvement

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Relationships of PBMC microRNA expression, plasma viral load, and CD4+ T-cell count in HIV-1-infected elite suppressors and viremic patients

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Dissecting the Biochemical and Transcriptomic Effects of a Locally Applied Heat Treatment on Developing Cabernet Sauvignon Grape Berries

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Two Closely Related Subclass II SnRK2 Protein Kinases Cooperatively Regulate Drought-Inducible Gene Expression

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Transcriptomic Analyses during the Transition from Biomass Production to Lipid Accumulation in the Oleaginous Yeast Yarrowia lipolytica

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Circulating biomarkers for detection of ovarian cancer and predicting cancer outcomes

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Paternal sperm DNA methylation associated with early signs of autism risk in an autism-enriched cohort

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Invasion by P. falciparum Merozoites Suggests a Hierarchy of Molecular Interactions

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Evolution of Stress-Regulated Gene Expression in Duplicate Genes of Arabidopsis thaliana

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Targeted DNA Sequencing from Autism Spectrum Disorder Brains Implicates Multiple Genetic Mechanisms

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Pyrethroid tolerance is associated with elevated expression of antioxidants and agricultural practice in Anopheles arabiensis sampled from an area of cotton fields in Northern Cameroon

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CD160 and PD-1 Co-Expression on HIV-Specific CD8 T Cells Defines a Subset with Advanced Dysfunction

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Microarray analysis identifies candidate genes for key roles in coral development

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GlobalANCOVA: exploration and assessment of gene group effects

Hummel, M., Meister, R., & Mansmann, U. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm531 · Cited by 148

RNA-Seq Transcriptome Profiling Identifies CRISPLD2 as a Glucocorticoid Responsive Gene that Modulates Cytokine Function in Airway Smooth Muscle Cells

Himes, B. E., Jiang, X., Wagner, P., Hu, R., Wang, Q., Klanderman, B. J., Whitaker, R. M., Duan, Q., Lasky-Su, J. A., Nikolos, C., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0099625 · Cited by 152

Genotype and time of day shape the Populus drought response

Wilkins, O., Waldron, L., Nahal-Bose, H. K., Provart, N. J., & Campbell, M. M. (2009) · The Plant Journal · doi:10.1111/j.1365-313x.2009.03993.x · Cited by 147

Pre-processing and differential expression analysis of Agilent microRNA arrays using the AgiMicroRna Bioconductor library

López‐Romero, P. (2011) · BMC Genomics · doi:10.1186/1471-2164-12-64 · Cited by 147

Circadian oscillation of gibberellin signaling in Arabidopsis

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Roles for blue light, jasmonate and nitric oxide in the regulation of dormancy and germination in wheat grain (Triticum aestivum L.)

Jacobsen, J. V., Barrero, J. M., Hughes, T., Julkowska, M., Taylor, J. M., Xu, Q., & Gubler, F. (2013) · Planta · doi:10.1007/s00425-013-1878-0 · Cited by 146

Characterizing Human Stem Cell–derived Sensory Neurons at the Single-cell Level Reveals Their Ion Channel Expression and Utility in Pain Research

Young, G. T., Gutteridge, A., Fox, H. D., Wilbrey, A. L., Cao, L., Cho, L. T. Y., Brown, A. R., Benn, C., Kammonen, L. R., Friedman, J., et al. (2014) · Molecular Therapy · doi:10.1038/mt.2014.86 · Cited by 147

Genomic occupancy of Runx2 with global expression profiling identifies a novel dimension to control of osteoblastogenesis

Wu, H., Whitfield, T. W., Gordon, J. A. R., Dobson, J. R., Tai, P. W. L., van Wijnen, A. J., Stein, J. L., Stein, G. S., & Lian, J. B. (2014) · Genome biology · doi:10.1186/gb-2014-15-3-r52 · Cited by 152

Hepatic glucose sensing is required to preserve β cell glucose competence

Seyer, P., Vallois, D., Poitry‐Yamate, C., Schütz, F., Metref, S., Tarussio, D., Maechler, P., Staels, B., Lanz, B., Rolf Gruetter, A., et al. (2013) · Journal of Clinical Investigation · doi:10.1172/jci65538 · Cited by 165

Oncogene-like addiction to aneuploidy in human cancers

Girish, V., Lakhani, A. A., Thompson, S. L., Scaduto, C. M., Brown, L. M., Hagenson, R. A., Sausville, E. L., Mendelson, B. E., Kandikuppa, P. K., Lukow, D. A., et al. (2023) · Science · doi:10.1126/science.adg4521 · Cited by 148

Dissection of Symbiosis and Organ Development by Integrated Transcriptome Analysis of Lotus japonicus Mutant and Wild-Type Plants

Høgslund, N., Radutoiu, S., Krusell, L., Voroshilova, V. A., Hannah, M. A., Goffard, N., Sánchez, D. H., Lippold, F., Ott, T., Sato, S., et al. (2009) · PLoS ONE · doi:10.1371/journal.pone.0006556 · Cited by 145

Glioblastoma Models Reveal the Connection between Adult Glial Progenitors and the Proneural Phenotype

Lei, L., Sonabend, A. M., Guarnieri, P., Soderquist, C. R., Ludwig, T. E., Rosenfeld, S. A., Bruce, J. N., & Canoll, P. (2011) · PLoS ONE · doi:10.1371/journal.pone.0020041 · Cited by 149

Comparative pan-cancer DNA methylation analysis reveals cancer common and specific patterns

Yang, X., Gao, L., & Zhang, S. (2016) · Briefings in Bioinformatics · doi:10.1093/bib/bbw063 · Cited by 147

Circulating MicroRNAs as Non-Invasive Biomarkers for Early Detection of Non-Small-Cell Lung Cancer

Wozniak, M. B., Scélo, G., Muller, D. C., Mukeria, A., Zaridze, D. G., & Brennan, P. (2015) · PLoS ONE · doi:10.1371/journal.pone.0125026 · Cited by 145

The arbuscular mycorrhizal status has an impact on the transcriptome profile and amino acid composition of tomato fruit

Salvioli, A., Zouari, I., Chalot, M., & Bonfante, P. (2012) · BMC Plant Biology · doi:10.1186/1471-2229-12-44 · Cited by 144

Cardiomyocyte-specific perilipin 5 overexpression leads to myocardial steatosis and modest cardiac dysfunction

Wang, H., Sreenivasan, U., Gong, D., O’Connell, K. A., Dabkowski, E. R., Hecker, P. A., Ionica, N., Кониг, М., Mahurkar, A., Sun, Y., et al. (2013) · Journal of Lipid Research · doi:10.1194/jlr.m032466 · Cited by 144

DNA Methylation of the Aryl Hydrocarbon Receptor Repressor Associations With Cigarette Smoking and Subclinical Atherosclerosis

Reynolds, L. M., Wan, M., Ding, J., Taylor, J. R., Lohman, K., Su, D., Bennett, B. D., Porter, D. K., Gimple, R. C., Pittman, G. S., et al. (2015) · Circulation Cardiovascular Genetics · doi:10.1161/circgenetics.115.001097 · Cited by 146

BioHMM: a heterogeneous hidden Markov model for segmenting array CGH data

Marioni, J. C., Thorne, N., & Tavaré, S. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl089 · Cited by 144

Robust global microRNA expression profiling using next-generation sequencing technologies

Tam, S., de Borja, R., Tsao, M., & McPherson, J. D. (2014) · Laboratory Investigation · doi:10.1038/labinvest.2013.157 · Cited by 147

Introgression of Novel Traits from a Wild Wheat Relative Improves Drought Adaptation in Wheat

Placido, D. F., Campbell, M. T., Folsom, J. J., Cui, X., Kruger, G. R., Baenziger, P. S., & Walia, H. (2013) · PLANT PHYSIOLOGY · doi:10.1104/pp.113.214262 · Cited by 149

Exploring the genetic basis of human population differences in DNA methylation and their causal impact on immune gene regulation

Husquin, L. T., Rotival, M., Fagny, M., Quach, H., Zidane, N., McEwen, L. M., MacIsaac, J. L., Kobor, M. S., Aschard, H., Patin, É., et al. (2018) · Genome biology · doi:10.1186/s13059-018-1601-3 · Cited by 149

Genome-wide analysis of PPARα activation in murine small intestine

Bünger, M., den Bosch, H. D. V.-V., van der Meijde, J., Kersten, S., Hooiveld, G. J. E. J., & Müller, M. M. (2007) · Physiological Genomics · doi:10.1152/physiolgenomics.00198.2006 · Cited by 145

Zebrafish mutants in the von Hippel-Lindau tumor suppressor display a hypoxic response and recapitulate key aspects of Chuvash polycythemia

van Rooijen, E., Voest, E. E., Logister, I., Korving, J., Schwerte, T., Schulte‐Merker, S., Giles, R. H., & van Eeden, F. J. (2009) · Blood · doi:10.1182/blood-2008-07-167890 · Cited by 146

Genome-Wide Identification of Human FOXP3 Target Genes in Natural Regulatory T Cells

Sadlon, T. J., Wilkinson, B. G., Pederson, S., Brown, C. Y., Bresatz, S., Gargett, T., Melville, E. L., Peng, K., D’Andrea, R. J., Glonek, G. G., et al. (2010) · The Journal of Immunology · doi:10.4049/jimmunol.1000082 · Cited by 146

The Fusarium graminearum Genome Reveals More Secondary Metabolite Gene Clusters and Hints of Horizontal Gene Transfer

Sieber, C. M. K., Lee, W., Wong, P., Münsterkötter, M., Mewes, H., Schmeitzl, C., Varga, E., Berthiller, F., Adam, G., & Güldener, U. (2014) · PLoS ONE · doi:10.1371/journal.pone.0110311 · Cited by 140

Transcript abundance profiles reveal larger and more complex responses of grapevine to chilling compared to osmotic and salinity stress

Tattersall, E. A. R., Grimplet, J., Deluc, L. G., Wheatley, M. D., Vincent, D., Osborne, C., Ergül, A., Lomen, E., Blank, R. R., Schlauch, K. A., et al. (2007) · Functional & Integrative Genomics · doi:10.1007/s10142-007-0051-x · Cited by 140

MicroRNA-143 down-regulates Hexokinase 2 in colon cancer cells

Gregersen, L. H., Skanderup, A. J., Frankel, L. B., Wen, J., Krogh, A., & Lund, A. H. (2012) · BMC Cancer · doi:10.1186/1471-2407-12-232 · Cited by 144

Targeting soluble tumor necrosis factor as a potential intervention to lower risk for late-onset Alzheimer’s disease associated with obesity, metabolic syndrome, and type 2 diabetes

Rodrigues, M. E. D. S., Houser, M. C., Walker, D. I., Jones, D. P., Chang, J., Barnum, C. J., & Tansey, M. G. (2019) · Alzheimer s Research & Therapy · doi:10.1186/s13195-019-0546-4 · Cited by 141

Intratumoural immune heterogeneity as a hallmark of tumour evolution and progression in hepatocellular carcinoma

Nguyen, P. H. D., Ma, S., Phua, C. Z. J., Kaya, N. A., Lai, H. L. H., Lim, C. J., Lim, J. Q., Wasser, M., Lai, L., Tam, W. L., et al. (2021) · Nature Communications · doi:10.1038/s41467-020-20171-7 · Cited by 142

Heavy metal resistance in Cupriavidus metallidurans CH34 is governed by an intricate transcriptional network

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Dominance and the evolutionary accumulation of cis - and trans -effects on gene expression

Lemos, B., Araripe, L. O., Fontanillas, P., & Hartl, D. L. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0805160105 · Cited by 140

Effects of palmitate on genome-wide mRNA expression and DNA methylation patterns in human pancreatic islets

Hall, E., Volkov, P., Dayeh, T., Bacos, K., Rönn, T., Nitert, M. D., & Ling, C. (2014) · BMC Medicine · doi:10.1186/1741-7015-12-103 · Cited by 145

Location-Specific Responses to Thermal Stress in Larvae of the Reef-Building Coral Montastraea faveolata

Polato, N. R., Voolstra, C. R., Schnetzer, J., DeSalvo, M. K., Randall, C. J., Szmant, A. M., Medina, M., & Baums, I. B. (2010) · PLoS ONE · doi:10.1371/journal.pone.0011221 · Cited by 138

Salicylic acid is an indispensable component of the Ny-1 resistance-gene-mediated response against Potato virus Y infection in potato

Baebler, Š., Witek, K., Petek, M., Stare, K., Tušek‐Žnidarič, M., Pompe‐Novak, M., Renaut, J., Szajko, K., Strzelczyk‐Żyta, D., Marczewski, W., et al. (2014) · Journal of Experimental Botany · doi:10.1093/jxb/ert447 · Cited by 138

Uncoupling phosphate deficiency from its major effects on growth and transcriptome via PHO1 expression in Arabidopsis

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Insight into the primary mode of action of TiO 2 nanoparticles on Escherichia coli in the dark

Sohm, B., Immel, F., Bauda, P., & Pagnout, C. (2014) · PROTEOMICS · doi:10.1002/pmic.201400101 · Cited by 138

The Effect of Acute and Chronic Social Stress on the Hippocampal Transcriptome in Mice

Stankiewicz, A. M., Gościk, J., Majewska, A., Swiergiel, A. H., & Juszczak, G. R. (2015) · PLoS ONE · doi:10.1371/journal.pone.0142195 · Cited by 145

Integrated genomic approaches identify major pathways and upstream regulators in late onset Alzheimer’s disease

Li, X., Long, J., He, T., Belshaw, R. D., & Scott, J. (2015) · Scientific Reports · doi:10.1038/srep12393 · Cited by 141

metagenomeSeq: Statistical analysis for sparse high-throughput sequencing

Paulson, J. N. (2017) · Cited by 138

Functional proteomic analysis of GS‐NS0 murine myeloma cell lines with varying recombinant monoclonal antibody production rate

Dinnis, D. M., Stansfield, S. H., Schlatter, S., Smales, C. M., Alete, D. E., Birch, J. R., Racher, A. J., Marshall, C. T., Nielsen, L. K., & James, D. C. (2006) · Biotechnology and Bioengineering · doi:10.1002/bit.20899 · Cited by 138

H3K4me1 marks DNA regions hypomethylated during aging in human stem and differentiated cellsPreprint

Fernandez-Fernandez, A., Bayón, G. F., Urdinguio, R. G., Toraño, E. G., García, M. G., Carella, A., Petrus-Reurer, S., Ferrero, C., Martinez-Camblor, P., Cubillo, I., et al. (2014) · Genome Research · doi:10.1101/gr.169011.113 · Cited by 140

Oncogenic CXCL10 signalling drives metastasis development and poor clinical outcome

Wightman, S. C., Uppal, A., Pitroda, S. P., Ganai, S., Burnette, B., Stack, M. E., Oshima, G., Khan, S. A., Huang, X., Posner, M. C., et al. (2015) · British Journal of Cancer · doi:10.1038/bjc.2015.193 · Cited by 137

Hydrogen peroxide primes heart regeneration with a derepression mechanism

Han, P., Zhou, X., Chang, N., Xiao, C., Yan, S., Ren, H., Yang, X., Zhang, M., Wu, Q., Tang, B., et al. (2014) · Cell Research · doi:10.1038/cr.2014.108 · Cited by 143

Classification of usual interstitial pneumonia in patients with interstitial lung disease: assessment of a machine learning approach using high-dimensional transcriptional data

Kim, S. Y., Diggans, J., Pankratz, D., Huang, J., Pagan, M., Sindy, N., Tom, E., Anderson, J. D., Choi, Y., Lynch, D. A., et al. (2015) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(15)00140-x · Cited by 137

Mechanisms of action of sacubitril/valsartan on cardiac remodeling: a systems biology approach

Egea, O. I., Gálvez‐Montón, C., Roura, S., Perea‐Gil, I., Prat‐Vidal, C., Soler‐Botija, C., & Bayés‐Genís, A. (2017) · npj Systems Biology and Applications · doi:10.1038/s41540-017-0013-4 · Cited by 137

A Phase II Study of Allogeneic GM-CSF–Transfected Pancreatic Tumor Vaccine (GVAX) with Ipilimumab as Maintenance Treatment for Metastatic Pancreatic Cancer

Wu, A. A., Bever, K. M., Ho, W. J., Fertig, E. J., Niu, N., Zheng, L., Parkinson, R. M., Durham, J. N., Onners, B., Ferguson, A. K., et al. (2020) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-20-1025 · Cited by 144

Optimization of miRNA-seq data preprocessing

Tam, S., Tsao, M., & McPherson, J. D. (2015) · Briefings in Bioinformatics · doi:10.1093/bib/bbv019 · Cited by 136

Molecular and Photosynthetic Responses to Prolonged Darkness and Subsequent Acclimation to Re-Illumination in the Diatom Phaeodactylum tricornutum

Nymark, M., Valle, K. C., Hancke, K., Winge, P., Andresen, K., Johnsen, G. H., Bones, A. M., & Brembu, T. (2013) · PLoS ONE · doi:10.1371/journal.pone.0058722 · Cited by 136

Exact and Approximate Area-Proportional Circular Venn and Euler Diagrams

Wilkinson, L. (2011) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2011.56 · Cited by 145

The recent escalation in strength of pyrethroid resistance in Anopheles coluzzi in West Africa is linked to increased expression of multiple gene families

Toé, K. H., N’Falé, S., Dabiré, R. K., Ranson, H., & Jones, C. M. (2015) · BMC Genomics · doi:10.1186/s12864-015-1342-6 · Cited by 141

MicroRNA profiling of Barrett's oesophagus and oesophageal adenocarcinoma

Wijnhoven, B. P. L., Hussey, D. J., Watson, D. I., Tsykin, A., Smith, C. M., & Michael, M. (2010) · British journal of surgery · doi:10.1002/bjs.7000 · Cited by 139

A portrait of copy-number polymorphism in Drosophila melanogaster

Dopman, E. B., & Hartl, D. L. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0709888104 · Cited by 136

β-catenin-independent WNT signaling in basal-like breast cancer and brain metastasis

Klemm, F., Bleckmann, A., Siam, L., Chuang, H., Rietkötter, E., Behme, D., Schulz, M., Schaffrinski, M., Schindler, S., Trümper, L. H. P., et al. (2010) · Carcinogenesis · doi:10.1093/carcin/bgq269 · Cited by 139

A multidimensional analysis of genes mutated in breast and colorectal cancersPreprint

Lin, J., Gan, C. M., Zhang, X., Jones, S., Sjöblom, T., Wood, L. D., Parsons, D. W., Papadopoulos, N., Kinzler, K. W., Vogelstein, B., et al. (2007) · Genome Research · doi:10.1101/gr.6431107 · Cited by 136

Transcriptional profiling of MnSOD-mediated lifespan extension in Drosophilareveals a species-general network of aging and metabolic genes

Curtis, C. N., Landis, G. N., Folk, D. G., Wehr, N. B., Hoe, N., Waskar, M., Abdueva, D. A., Skvortsov, D., Ford, D., Luu, A., et al. (2007) · Genome biology · doi:10.1186/gb-2007-8-12-r262 · Cited by 135

Prediction model for aneuploidy in early human embryo development revealed by single-cell analysis

Vera-Rodríguez, M., Chavez, S. L., Rubio, C., Pera, R. A. R., & Simón, C. (2015) · Nature Communications · doi:10.1038/ncomms8601 · Cited by 138

Epigenome-wide meta-analysis of PTSD across 10 military and civilian cohorts identifies methylation changes in AHRR

Smith, A. K., Ratanatharathorn, A. D., Maihofer, A. X., Naviaux, R. K., Aiello, A. E., Amstadter, A. B., Ashley‐Koch, A. E., Baker, D. G., Beckham, J. C., Boks, M. P., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-19615-x · Cited by 141

Multi-omics analysis of innate and adaptive responses to BCG vaccination reveals epigenetic cell states that predict trained immunity

Moorlag, S. J. C. F. M., Folkman, L., ter Horst, R., Krausgruber, T., Barreca, D., Schuster, L. C., Fife, V. E. R., Matzaraki, V., Li, W., Reichl, S., et al. (2024) · Immunity · doi:10.1016/j.immuni.2023.12.005 · Cited by 145

Two Distinct Repressive Mechanisms for Histone 3 Lysine 4 Methylation through Promoting 3′-End Antisense Transcription

Margaritis, T., Oréal, V., Brabers, N., Maestroni, L., Vitaliano-Prunier, A., Benschop, J. J., van Hooff, S. R., van Leenen, D., Dargemont, C., Géli, V., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002952 · Cited by 142

PRDM14 promotes active DNA demethylation through the Ten-eleven translocation (TET)-mediated base excision repair pathway in embryonic stem cells

Okashita, N., Kumaki, Y., Ebi, K., Nishi, M., Okamoto, Y., Nakayama, M., Hashimoto, S., Nakamura, T., Sugasawa, K., Kojima, N., et al. (2013) · Development · doi:10.1242/dev.099622 · Cited by 134

A 3′-untranslated region KRAS variant and triple-negative breast cancer: a case-control and genetic analysis

Paranjape, T., Heneghan, H., Lindner, R. M., Keane, F. K., Hoffman, A. E., Hollestelle, A., Dorairaj, J. J., Geyda, K., Pelletier, C., Nallur, S. V., et al. (2011) · The Lancet Oncology · doi:10.1016/s1470-2045(11)70044-4 · Cited by 134

Use of Metagenomic Shotgun Sequencing Technology To Detect Foodborne Pathogens within the Microbiome of the Beef Production Chain

Yang, X., Noyes, N. R., Doster, E., Martin, J. N., Linke, L., Magnuson, R. J., Yang, H., Geornaras, I., Woerner, D. R., Jones, K. L., et al. (2016) · Applied and Environmental Microbiology · doi:10.1128/aem.00078-16 · Cited by 143

Potential biomarkers and therapeutic targets in cervical cancer: Insights from the meta-analysis of transcriptomics data within network biomedicine perspective

Kori, M., & Arğa, K. Y. (2018) · PLoS ONE · doi:10.1371/journal.pone.0200717 · Cited by 139

Humoral Immune Response against Nontargeted Tumor Antigens after Treatment with Sipuleucel-T and Its Association with Improved Clinical Outcome

GuhaThakurta, D., Sheikh, N. A., Fan, L.-Q., Kandadi, H., Meagher, T. C., Hall, S. J., Kantoff, P. W., Higano, C. S., Small, E. J., Gardner, T. A., et al. (2015) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-14-2334 · Cited by 133

Time‐series resolution of gradual nitrogen starvation and its impact on photosynthesis in the cyanobacterium Synechocystis PCC 6803

Krasikov, V., Aguirre‐von‐Wobeser, E., Dekker, H. L., Huisman, J., & Matthijs, H. C. P. (2012) · Physiologia Plantarum · doi:10.1111/j.1399-3054.2012.01585.x · Cited by 133

Early life microbial colonization of the gut and intestinal development differ between genetically divergent broiler lines

Schokker, D., Veninga, G., Vastenhouw, S. A., Bossers, A., de Bree, F. M., Kaal-Lansbergen, L. M. T. E., Rebel, J. M. J., & Smits, M. A. (2015) · BMC Genomics · doi:10.1186/s12864-015-1646-6 · Cited by 137

Selective Tropism of Seneca Valley Virus for Variant Subtype Small Cell Lung Cancer

Poirier, J. T., Dobromilskaya, I., Moriarty, W. F., Peacock, C. D., Hann, C. L., & Rudin, C. M. (2013) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djt130 · Cited by 133

Predicting Hub Genes Associated with Cervical Cancer through Gene Co-Expression Networks

Deng, S.-P., Zhu, L., & Huang, D.-S. (2015) · IEEE Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2015.2476790 · Cited by 134

Small RNAs and the regulation of cis-natural antisense transcripts in Arabidopsis

Jin, H., Vacic, V., Girke, T., Lonardi, S., & Zhu, J. (2008) · BMC Molecular Biology · doi:10.1186/1471-2199-9-6 · Cited by 133

Inactivating CUX1 mutations promote tumorigenesis

Wong, C. C., Martin, S., Rust, A. G., Rashid, M., Alifrangis, C., Alexandrov, L. B., Tiffen, J. C., Kober, C., Green, A. R., Massie, C. E., et al. (2013) · Nature Genetics · doi:10.1038/ng.2846 · Cited by 135

Functional Genomics Reveals Dysregulation of Cortical Olfactory Receptors in Parkinson Disease: Novel Putative Chemoreceptors in the Human Brain

Garcia‐Esparcia, P., Schlüter, A., Carmona, M., Moreno, J. R., Ansoleaga, B., Torrejón-Escribano, B., Gustincich, S., Pujol, A., & Ferrer, I. (2013) · Journal of Neuropathology & Experimental Neurology · doi:10.1097/nen.0b013e318294fd76 · Cited by 132

Analysis of epigenetic changes in survivors of preterm birth reveals the effect of gestational age and evidence for a long term legacy

Cruickshank, M. N., Oshlack, A., Theda, C., Davis, P. G., Martino, D., Sheehan, P. M., Dai, Y., Saffery, R., Doyle, L. W., & Craig, J. M. (2013) · Genome Medicine · doi:10.1186/gm500 · Cited by 136

The prediction of early preeclampsia: Results from a longitudinal proteomics study

Tarca, A. L., Romero, R. J., Benshalom-Tirosh, N., Than, N. G., Gudicha, D. W., Done, B., Pacora, P., Chaiworapongsa, T., Panaitescu, B., Tirosh, D., et al. (2019) · PLoS ONE · doi:10.1371/journal.pone.0217273 · Cited by 133

Water Deficit Modulates the Response ofVitis viniferato the Pierce's Disease PathogenXylella fastidiosa

Choi, H., Iandolino, A. B., da Silva, F. G., & Cook, D. R. (2013) · Molecular Plant-Microbe Interactions · doi:10.1094/mpmi-09-12-0217-r · Cited by 138

Receptor-type guanylate cyclase is required for carbon dioxide sensation by Caenorhabditis elegans

Hallem, E. A., Spencer, W. C., McWhirter, R. D., Zeller, G., Henz, S. R., Rätsch, G., Miller, D. M., Horvitz, H. R., Sternberg, P. W., & Ringstad, N. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1017354108 · Cited by 131

Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size

Yu, D., Huber, W. K., & Vitek, O. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt143 · Cited by 134

Specificity and transcriptional activity of microbiota associated with low and high microbial abundance sponges from the Red Sea

Moitinho‐Silva, L., Bayer, K., Cannistraci, C. V., Giles, E. C., Ryu, T., Seridi, L., Ravasi, T., & Hentschel, U. (2013) · Molecular Ecology · doi:10.1111/mec.12365 · Cited by 130

Bayesian probit regression model for the diagnosis of pulmonary fibrosis: proof-of-principle

Meltzer, E. B., Barry, W. T., D’Amico, T. A., Davis, R. D., Lin, S. S., Onaitis, M. W., Morrison, L. D., Sporn, T. A., Steele, M. P., & Noble, P. W. (2011) · BMC Medical Genomics · doi:10.1186/1755-8794-4-70 · Cited by 130

Identification of genes involved in cell wall biogenesis in grasses by differential gene expression profiling of elongating and non-elongating maize internodes

Bosch, M., Mayer, C., Cookson, A., & Donnison, I. S. (2011) · Journal of Experimental Botany · doi:10.1093/jxb/err045 · Cited by 130

TCP15 modulates cytokinin and auxin responses during gynoecium development in Arabidopsis

Lucero, L. E., Uberti‐Manassero, N. G., Arce, A. L., Colombatti, F., Alemano, S. G., & González, D. H. (2015) · The Plant Journal · doi:10.1111/tpj.12992 · Cited by 129

Breaking the waves: improved detection of copy number variation from microarray-based comparative genomic hybridization

Marioni, J. C., Thorne, N., Valsesia, A., Fitzgerald, T. W., Redon, R., Fiegler, H., Andrews, T. D., Stranger, B. E., Lynch, A. G., Dermitzakis, E. T., et al. (2007) · Genome biology · doi:10.1186/gb-2007-8-10-r228 · Cited by 129

Genome-wide DNA methylation analysis identifies hypomethylated genes regulated by FOXP3 in human regulatory T cells

Zhang, Y., Maksimovic, J., Naselli, G., Qian, J., Chopin, M., Blewitt, M. E., Oshlack, A., & Harrison, L. C. (2013) · Blood · doi:10.1182/blood-2013-02-481788 · Cited by 132

Common Structural and Epigenetic Changes in the Genome of Castration-Resistant Prostate Cancer

Friedlander, T. W., Roy, R., Tomlins, S. A., Ngo, V., Kobayashi, Y., Azameera, A., Rubin, M. A., Pienta, K. J., Chinnaiyan, A. M., Ittmann, M., et al. (2011) · Cancer Research · doi:10.1158/0008-5472.can-11-2079 · Cited by 129

GPCRomics: GPCR Expression in Cancer Cells and Tumors Identifies New, Potential Biomarkers and Therapeutic Targets

Insel, P. A., Sriram, K., Wiley, S. Z., Wilderman, A. S., Katakia, T., McCann, T., Yokouchi, H., Zhang, L., Corriden, R., Liu, D., et al. (2018) · Frontiers in Pharmacology · doi:10.3389/fphar.2018.00431 · Cited by 129

DNA hypermethylation associated with upregulated gene expression in prostate cancer demonstrates the diversity of epigenetic regulation

Rauluševičiūtė, I., Drabløs, F., & Rye, M. B. (2020) · BMC Medical Genomics · doi:10.1186/s12920-020-0657-6 · Cited by 129

Construction of TME and Identification of crosstalk between malignant cells and macrophages by SPP1 in hepatocellular carcinoma

Liu, L., Zhang, R., Deng, J., Dai, X., Zhu, X., Fu, Q., Zhang, H., Tong, Z., Zhao, P., Fang, W. J., et al. (2021) · Cancer Immunology Immunotherapy · doi:10.1007/s00262-021-02967-8 · Cited by 129

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)