The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.
limma: Linear Models for Microarray Data
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“This approach accounts for both the within and between group variation when testing for differences between groups.”
In the citing paper
“Next, filtered read counts from all groups were normalized together by the trimmed mean of the M-values normalization method (TMM) to reduce the likelihood of unequal variances between groups [101].”
In the citing paper
“The limma package is a core component of Bioconductor, an R-based open-source software development project in statistical genomics (1,2).”
From limma powers differential expression analyses for RNA-sequencing and microarray studies (2015) · cites this paper as [2]
Citations
Cites
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
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
Self-citationHuber, W., von Heydebreck, A., Sültmann, H., Poustka, A., & Vingron, M. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_1.s96 · Cited by 2,440
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
Use of within-array replicate spots for assessing differential expression in microarray experiments
Smyth, G. K., Michaud, J., & Scott, H. S. (2005) · Computer applications in the biosciences · doi:10.1093/bioinformatics/bti270 · Cited by 1,406
Self-citationAnalysis of Messy Data, Volume I: Designed Experiments
Schmee, J., Milliken, G. A., & Johnson, D. E. (1985) · Technometrics · doi:10.2307/1270212 · Cited by 922
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
Self-citationParameter estimation for the calibration and variance stabilization of microarray data
Huber, W. K., von Heydebreck, A., Sueltmann, H., Poustka, A., & Vingron, M. (2003) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1008 · Cited by 185
Design and analysis of comparative microarray experiments
Speed, T. P. (2003) · doi:10.1201/9780203011232-9 · Cited by 67
Cited by
Sorted by citations
Items 101–200 of 1,041
Interleukin-6 as a Therapeutic Target in Human Ovarian Cancer
Coward, J. I. G., Kulbe, H., Chakravarty, P., Leader, D., Vassileva, V., Leinster, D. A., Thompson, R. D., Schioppa, T., Nemeth, J., VERMEULEN, J. T., et al. (2011) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-11-0945 · Cited by 397
Sevenich, L., Bowman, R. L., Mason, S. D., Quail, D. F., Rapaport, F., Elie, B. T., Brogi, E., Brastianos, P. K., Hahn, W. C., Holsinger, L. J., et al. (2014) · Nature Cell Biology · doi:10.1038/ncb3011 · Cited by 389
Lehne, B., Drong, A. W., Loh, M., Zhang, W., Scott, W. R., Tan, S.-T., Afzal, U., Scott, J., Jarvelin, M.-R., Elliott, P., et al. (2015) · Genome biology · doi:10.1186/s13059-015-0600-x · Cited by 380
The Molecular Signature of Tissue Resident Memory CD8 T Cells Isolated from the Brain
Wakim, L. M., Davis, A. S. W., Liu, R., Hu, Y., Villadangos, J. A., Smyth, G. K., & Bevan, M. J. (2012) · The Journal of Immunology · doi:10.4049/jimmunol.1201305 · Cited by 381
Self-citationRyabov, E. V., Wood, G. R., Fannon, J. M., Moore, J. D., Bull, J. C., Chandler, D., Mead, A., Burroughs, N. J., & Evans, D. J. (2014) · PLoS Pathogens · doi:10.1371/journal.ppat.1004230 · Cited by 363
L1000CDS2: LINCS L1000 characteristic direction signatures search engine
Duan, Q., Reid, S. P., Clark, N. R., Wang, Z., Fernandez, N., Rouillard, A. D., Readhead, B., Tritsch, S. R., Hodos, R. A., Hafner, M. A., et al. (2016) · npj Systems Biology and Applications · doi:10.1038/npjsba.2016.15 · Cited by 367
A general modular framework for gene set enrichment analysis
Ackermann, M., & Strimmer, K. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-47 · Cited by 358
Crosstalk Between the MSI Status and Tumor Microenvironment in Colorectal Cancer
Lin, A., Zhang, J., & Luo, P. (2020) · Frontiers in Immunology · doi:10.3389/fimmu.2020.02039 · Cited by 358
MicroRNA-regulated pathways associated with endometriosis
Ohlsson Teague, E. M. C., Van der Hoek, K. H., Van der Hoek, M. B., Perry, N., Wagaarachchi, P., Robertson, S. A., Print, C. G., & Hull, L. M. (2009) · Molecular Endocrinology · doi:10.1210/me.2008-0387 · Cited by 357
Müller, P., Warr, E., Stevenson, B. J., Pignatelli, P. M., Morgan, J. C., Steven, A., Yawson, A. E., Mitchell, S. N., Ranson, H., Hemingway, J., et al. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000286 · Cited by 355
Oh, E., Kang, H.-J., Yamaguchi, S., Park, J., Lee, D., Kamiya, Y., & Choi, G. (2009) · The Plant Cell · doi:10.1105/tpc.108.064691 · Cited by 355
Peripheral blood gene expression: it all boils down to the RNA collection tubes
Menke, A., Rex‐Haffner, M., Klengel, T., Binder, E. B., & Mehta, D. (2012) · BMC Research Notes · doi:10.1186/1756-0500-5-1 · Cited by 352
Drug repositioning: a machine-learning approach through data integration
Napolitano, F., Zhao, Y., Moreira, V. M., Tagliaferri, R., Kere, J., D’Amato, M., & Greco, D. (2013) · Journal of Cheminformatics · doi:10.1186/1758-2946-5-30 · Cited by 349
Spatiotemporal Co-Dependency between Macrophages and Exhausted CD8 + T Cells in Cancer
Kersten, K., Hu, K. H., Combes, A. J., Samad, B., Harwin, T., Ray, A., Rao, A. A., Cai, E., Marchuk, K., Artichoker, J., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2022.05.004 · Cited by 357
Déjà vu in proteomics. A hit parade of repeatedly identified differentially expressed proteins
Petrák, J., Ivánek, R., Toman, O., Čmejla, R., Čmejlová, J., Vyoral, D., Živný, J., & Vulpe, C. D. (2008) · PROTEOMICS · doi:10.1002/pmic.200700919 · Cited by 362
microRNA‐101 is a potent inhibitor of autophagy
Frankel, L. B., Wen, J., Lees, M., Høyer‐Hansen, M., Farkas, T., Krogh, A., Jäättelä, M., & Lund, A. H. (2011) · The EMBO Journal · doi:10.1038/emboj.2011.331 · Cited by 312
Microarray and genetic analysis of electron transfer to electrodes in Geobacter sulfurreducens
Holmes, D. E., Chaudhuri, S. K., Nevin, K. P., Mehta, T., Methé, B. A., Liu, A., Ward, J. E., Woodard, T. L., Webster, J., & Lovley, D. R. (2006) · Environmental Microbiology · doi:10.1111/j.1462-2920.2006.01065.x · Cited by 345
Interpretable dimensionality reduction of single cell transcriptome data with deep generative models
Ding, J., Condon, A., & Shah, S. P. (2018) · Nature Communications · doi:10.1038/s41467-018-04368-5 · Cited by 337
Usadel, B., Nagel, A., Steinhauser, D., Gibon, Y., Bläsing, O. E., Redestig, H., Sreenivasulu, N., Krall, L., Hannah, M. A., Porée, F., et al. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-535 · Cited by 335
Zingg, D., Debbache, J., Schaefer, S. M., Tuncer, E., Frommel, S. C., Cheng, P. F., Arenas-Ramirez, N., Häusel, J., Zhang, Y., Bonalli, M., et al. (2015) · Nature Communications · doi:10.1038/ncomms7051 · Cited by 331
Conserved epigenetic sensitivity to early life experience in the rat and human hippocampus
Suderman, M., McGowan, P. O., Sasaki, A., Huang, T. C. T., Hallett, M. T., Meaney, M. J., Turecki, G., & Szyf, M. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1121260109 · Cited by 327
Kuhn, A., Goldstein, D. R., Hodges, A., Strand, A. D., Sengstag, T., Kooperberg, C. L., Bečanović, K., Pouladi, M. A., Sathasivam, K., Cha, J.-H. J., et al. (2007) · Human Molecular Genetics · doi:10.1093/hmg/ddm133 · Cited by 327
Robin, J. D., Ludlow, A. T., Batten, K. G., Magdinier, F., Stadler, G., Wagner, K. R., Shay, J. W., & Wright, W. E. (2014) · Genes & Development · doi:10.1101/gad.251041.114 · Cited by 343
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
Rice MADS3 Regulates ROS Homeostasis during Late Anther Development
Hu, L., Liang, W., Yin, C., Cui, X., Zong, J., Wang, X., Hu, J., & Zhang, D. (2011) · The Plant Cell · doi:10.1105/tpc.110.074369 · Cited by 324
Patterson, K., Çakmak, T., COOPER, A., Lager, I., Rasmusson, A. G., & Escobar, M. A. (2010) · Plant Cell & Environment · doi:10.1111/j.1365-3040.2010.02158.x · Cited by 324
Medina, I., Carbonell‐Caballero, J., Pulido, L. J., Madeira, S. C., Götz, S., Conesa, A., rraga, J. ⁄. N. T. ⁄., Pascual-Montano, A., Nogales‐Cadenas, R., Santoyo‐López, J., et al. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq388 · Cited by 331
Expression profiling in primates reveals a rapid evolution of human transcription factors
Gilad, Y., Oshlack, A., Smyth, G. K., Speed, T. P., & White, K. P. (2006) · Nature · doi:10.1038/nature04559 · Cited by 323
Self-citationCommon patterns and disease-related signatures in tuberculosis and sarcoidosis
Maertzdorf, J., Weiner, J. M., Mollenkopf, H., T. Accelerating Medicines Partnership in RA SLE Network, Bauer, T. T., Prasse, A., Müller–Quernheim, J., Kaufmann, S. H. E., Bellinger, O., Diel, R., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1121072109 · Cited by 320
Chin, S., Teschendorff, A. E., Marioni, J. C., Wang, Y., Barbosa‐Morais, N. L., Thorne, N., Costa, J. L., Pinder, S. E., van de Wiel, M. A., Green, A. R., et al. (2007) · Genome biology · doi:10.1186/gb-2007-8-10-r215 · Cited by 323
Leahy, S. C., Kelly, W. J., Altermann, E., Ronimus, R. S., Yeoman, C. J., Pacheco, D. M., Li, D., Kong, Z., McTavish, S. M., Sang, C., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0008926 · Cited by 318
Li, H., Yuan, Z., Vizcay‐Barrena, G., Yang, C., Liang, W., Zong, J., Wilson, Z. A., & Zhang, D. (2011) · PLANT PHYSIOLOGY · doi:10.1104/pp.111.175760 · Cited by 320
Host-cell sensors for Plasmodium activate innate immunity against liver-stage infection
Liehl, P., Zuzarte-Luís, V., Chan, J., Zillinger, T., Baptista, F., Carapau, D., Konert, M., Hanson, K. K., Carret, C., Lassnig, C., et al. (2014) · Nature Medicine · doi:10.1038/nm.3424 · Cited by 313
Polyester : simulating RNA-seq datasets with differential transcript expression
Frazee, A. C., Jaffe, A. E., Langmead, B., & Leek, J. T. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv272 · Cited by 313
The signature of maternal rearing in the methylome in rhesus macaque prefrontal cortex and T cells
Provençal, N., Suderman, M. J., Guillemin, C., Massart, R., Ruggiero, A., Wang, D., Bennett, A. J., Pierre, P. J., Friedman, D. P., Côté, S. M., et al. (2012) · The Journal of Neuroscience · doi:10.1523/jneurosci.1470-12.2012 · Cited by 312
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
Self-citationZhou, J., Wang, X., Jiao, Y., Qin, Y., Liu, X., He, K., Chen, C., Ma, L., Wang, J., Xiong, L., et al. (2007) · Plant Molecular Biology · doi:10.1007/s11103-006-9111-1 · Cited by 315
Effects of Vendor and Genetic Background on the Composition of the Fecal Microbiota of Inbred Mice
Ericsson, A. C., Davis, J. W., Spollen, W. G., Bivens, N. J., Givan, S. A., Hagan, C. E., McIntosh, M., & Franklin, C. L. (2015) · PLoS ONE · doi:10.1371/journal.pone.0116704 · Cited by 321
The Hippo pathway transcriptional co-activator, YAP, is an ovarian cancer oncogene
Zhang, X., George, J., Deb, S., Degoutin, J. L., Takano, E. A., Fox, S. B., Chenevix‐Trench, G., Bowtell, D. D. L., & Harvey, K. F. (2011) · Oncogene · doi:10.1038/onc.2011.8 · Cited by 310
Forde, N., Beltman, M. E., Duffy, G. B., Duffy, P. E., Mehta, J. P., Gaora, P. Ó., ROCHE, J. F., Lonergan, P., & Crowe, M. A. (2010) · Biology of Reproduction · doi:10.1095/biolreprod.110.085910 · Cited by 308
Libault, M., Farmer, A. D., Brechenmacher, L., Drnevich, J. M., Langley, R. J., Bilgin, D. D., Radwan, O. E., Neece, D. J., Clough, S. J., May, G. D., et al. (2009) · PLANT PHYSIOLOGY · doi:10.1104/pp.109.148379 · Cited by 307
miRNA-mRNA Integrated Analysis Reveals Roles for miRNAs in Primary Breast Tumors
Enerly, E., Steinfeld, I., Sahlberg, K. K., Leivonen, S., Aure, M. R. R., Russnes, H. G., Rønneberg, J. A., Johnsen, H., Navon, R., Rødland, E. A., et al. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016915 · Cited by 306
Genome-wide DNA methylation analysis of human brain tissue from schizophrenia patients
Wockner, L. F., Noble, E. P., Lawford, B. R., Young, R. M., Morris, C. P., Whitehall, V., & Voisey, J. (2014) · Translational Psychiatry · doi:10.1038/tp.2013.111 · Cited by 315
An ENU-induced mutation of miR-96 associated with progressive hearing loss in mice
Lewis, M. A., Quint, E., Glazier, A. M., Fuchs, H., De Angelis, M. H., Langford, C., van Dongen, S., Abreu-Goodger, C., Piipari, M., Redshaw, N., et al. (2009) · Nature Genetics · doi:10.1038/ng.369 · Cited by 302
Analysis of microarray experiments of gene expression profiling
Tarca, A. L., Romero, R. J., & Drăghici, S. (2006) · American Journal of Obstetrics and Gynecology · doi:10.1016/j.ajog.2006.07.001 · Cited by 312
Fröhlich, D., Kuo, W. P., Frühbeis, C., Sun, J.-J., Zehendner, C. M., Luhmann, H. J., Pinto, S., Toedling, J., Trotter, J., & Krämer-Albers, E.-M. (2014) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2013.0510 · Cited by 313
Wegert, J., Ishaque, N., Vardapour, R., Geörg, C., Gu, Z., Bieg, M., Ziegler, B., Bausenwein, S., Nourkami, N., Ludwig, N., et al. (2015) · Cancer Cell · doi:10.1016/j.ccell.2015.01.002 · Cited by 304
Linkies, A., Müller, K., Morris, K., Turečková, V., Wenk, M., Cadman, C. S. C., Corbineau, F., Strnad, M., Lynn, J. R., Finch‐Savage, W. E., et al. (2009) · The Plant Cell · doi:10.1105/tpc.109.070201 · Cited by 299
Ribeiro, E. S., Gomes, G., Greco, L. F., Cerri, R. L. A., Vieira-Neto, A., Monteiro, P. L. J., de Lima, F. S., Bisinotto, R. S., Thatcher, W. W., & Santos, J. E. P. (2015) · Journal of Dairy Science · doi:10.3168/jds.2015-10337 · Cited by 299
BioJupies: Automated Generation of Interactive Notebooks for RNA-Seq Data Analysis in the Cloud
Torre, D., Lachmann, A., & Ma’ayan, A. (2018) · Cell Systems · doi:10.1016/j.cels.2018.10.007 · Cited by 301
Josset, L., Menachery, V. D., Gralinski, L. E., Agnihothram, S., Sova, P., Carter, V. S., Yount, B. L., Graham, R. L., Baric, R. S., & Katze, M. G. (2013) · mBio · doi:10.1128/mbio.00165-13 · Cited by 299
A systematic evaluation of single-cell RNA-sequencing imputation methods
Hou, W., Ji, Z., Ji, H., & Hicks, S. C. (2020) · Genome biology · doi:10.1186/s13059-020-02132-x · Cited by 307
Lazear, H. M., Lancaster, A., Wilkins, C., Suthar, M. S., Huang, A., Vick, S. C., Clepper, L., Thackray, L., Brassil, M. M., Virgin, H. W., et al. (2013) · PLoS Pathogens · doi:10.1371/journal.ppat.1003118 · Cited by 296
Ellis, L., Pan, Y., Smyth, G. K., George, D. J., McCormack, C. J., Williams-Truax, R., Mita, M. M., Beck, J., Burris, H. A., Ryan, G. F., et al. (2008) · Clinical Cancer Research · doi:10.1158/1078-0432.ccr-07-4262 · Cited by 296
Self-citationMas, V. R., Maluf, D. G., Archer, K. J., Yanek, K. C., Kong, X., Kulik, L., Freise, C. E., Olthoff, K. M., Ghobrial, R. M., McIver, P., et al. (2009) · Molecular Medicine · doi:10.2119/molmed.2008.00110 · Cited by 293
Kobayashi, K., Yasuno, N., Sato, Y., Yoda, M., Yamazaki, R., Kimizu, M., Yoshida, H., Nagamura, Y., & Kyozuka, J. (2012) · The Plant Cell · doi:10.1105/tpc.112.097105 · Cited by 292
Canine tumor cross-species genomics uncovers targets linked to osteosarcoma progression
Paoloni, M., Davis, S., Lana, S., Withrow, S., Sangiorgi, L., Picci, P., Hewitt, S., Triche, T., Meltzer, P., & Khanna, C. (2009) · BMC Genomics · doi:10.1186/1471-2164-10-625 · Cited by 291
Thomas, E. A., Coppola, G., Desplats, P., Tang, B., Soragni, E., Burnett, R., Gao, F., Fitzgerald, K. M., Borok, J. F., Herman, D., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0804249105 · Cited by 293
Koul, A., Vranckx, L., Dhar, N., Göhlmann, H. W. H., Özdemir, E., Neefs, J., Schulz, M., Lü, P., Mørtz, E., McKinney, J. D., et al. (2014) · Nature Communications · doi:10.1038/ncomms4369 · Cited by 298
Nishimura, N., Yoshida, T., Kitahata, N., Asami, T., Shinozaki, K., & Hirayama, T. (2007) · The Plant Journal · doi:10.1111/j.1365-313x.2007.03107.x · Cited by 293
Li, J., Besseau, S., Törönen, P., Sipari, N., Kollist, H., Holm, L., & Palva, E. T. (2013) · New Phytologist · doi:10.1111/nph.12378 · Cited by 288
Lehne, B. C., Drong, A., Loh, M. C. S., Zhang, W., Scott, W. R., Tan, S.-T., Afzal, U., Schulz, R., Scott, J., Järvelin, M., et al. (2016) · Genome biology · doi:10.1186/s13059-016-0934-z · Cited by 284
Effect of aspirin and NSAIDs on risk and survival from colorectal cancer
Din, F. V. N., Τheodoratou, E., Farrington, S. M., Tenesa, A., Barnetson, R. A., Cetnarskyj, R., Stark, L. A., Porteous, M. E., Campbell, H., & Dunlop, M. G. (2010) · Gut · doi:10.1136/gut.2009.203000 · Cited by 282
A comparison of statistical methods for detecting differentially expressed genes from RNA‐seq data
Kvam, V. M., Liu, P., & Si, Y. (2012) · American Journal of Botany · doi:10.3732/ajb.1100340 · Cited by 281
Differential Placental Gene Expression in Severe Preeclampsia
Sitras, V., Paulssen, R. H., Grønaas, H., Leirvik, J., Hanssen, T. A., Vårtun, Å., & Acharya, G. (2009) · Placenta · doi:10.1016/j.placenta.2009.01.012 · Cited by 286
Sebestyén, E., Singh, B., Miñana, B., Pagès, A., Mateo, F., Pujana, M. A., Valcárcel, J., & Eyras, E. (2016) · Genome Research · doi:10.1101/gr.199935.115 · Cited by 276
Whole-cell response to nitrogen deprivation in the diatom Phaeodactylum tricornutum
Alipanah, L., Rohloff, J., Winge, P., Bones, A. M., & Brembu, T. (2015) · Journal of Experimental Botany · doi:10.1093/jxb/erv340 · Cited by 294
ATF4 is an oxidative stress–inducible, prodeath transcription factor in neurons in vitro and in vivo
Lange, P. S., Chavez, J. C., Pinto, J. T., Coppola, G., Sun, C.-W., Townes, T. M., Geschwind, D. H., & Ratan, R. R. (2008) · The Journal of Experimental Medicine · doi:10.1084/jem.20071460 · Cited by 272
Major Cellular and Physiological Impacts of Ocean Acidification on a Reef Building Coral
Kaniewska, P., Campbell, P. R., Kline, D. I., Rodríguez‐Lanetty, M., Miller, D. J., Dove, S., & Hoegh‐Guldberg, O. (2012) · PLoS ONE · doi:10.1371/journal.pone.0034659 · Cited by 282
Gordon, L., Joo, J. E., Powell, J. E., Ollikainen, M., Novakovic, B., Li, X., Andronikos, R. H., Cruickshank, M. N., Conneely, K. N., Smith, A. K., et al. (2012) · Genome Research · doi:10.1101/gr.136598.111 · Cited by 276
Broad defects in epidermal cornification in atopic dermatitis identified through genomic analysis
Guttman-Yassky, E., Suárez-Fariñas, M., Chiricozzi, A., Nograles, K. E., Shemer, A., Fuentes-Duculan, J., Cardinale, I., Lin, P., Bergman, R., Bowcock, A. M., et al. (2009) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2009.09.031 · Cited by 268
Walker, B. A., Wardell, C. P., Chiecchio, L., Smith, E. M., Boyd, K. D., Neri, A., Davies, F. E., Ross, F. M., & Morgan, G. J. (2011) · Blood · doi:10.1182/blood-2010-04-279539 · Cited by 267
Howe, E., Holton, K. M., Nair, S. J., Schlauch, D., Sinha, R., & Quackenbush, J. F. (2010) · Springer eBooks · doi:10.1007/978-1-4419-5714-6_15 · Cited by 270
Hewezi, T., Maier, T. R., Nettleton, D. S., & Baum, T. J. (2012) · PLANT PHYSIOLOGY · doi:10.1104/pp.112.193649 · Cited by 264
Normalyzer: A Tool for Rapid Evaluation of Normalization Methods for Omics Data Sets
Chawade, A., Alexandersson, E., & Levander, F. (2014) · Journal of Proteome Research · doi:10.1021/pr401264n · Cited by 264
Todgham, A. E., & Hofmann, G. E. (2009) · Journal of Experimental Biology · doi:10.1242/jeb.032540 · Cited by 269
Yaari, G., Bolen, C. R., Thakar, J., & Kleinstein, S. H. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt660 · Cited by 269
Identification of differentially expressed genes between osteoblasts and osteocytes
Paić, F., Igwe, J. C., Nori, R., Kronenberg, M. S., Franceschetti, T., Harrington, P., Kuo, L., Shin, D., Rowe, D. W., Harris, S. E., et al. (2009) · Bone · doi:10.1016/j.bone.2009.06.010 · Cited by 271
Breton, C. V., Marsit, C. J., Faustman, E. M., Nadeau, K. C., Goodrich, J. M., Dolinoy, D. C., Herbstman, J. B., Holland, N., LaSalle, J. M., Schmidt, R. J., et al. (2017) · Environmental Health Perspectives · doi:10.1289/ehp595 · Cited by 271
Cancer transcriptome profiling at the juncture of clinical translation
Cieslik, M. P., & Chinnaiyan, A. M. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2017.96 · Cited by 266
Berkovic, S. F., Dibbens, L. M., Oshlack, A., Silver, J. D., Katerelos, M., Vears, D. F., Lüllmann‐Rauch, R., Blanz, J., Zhang, K. W., Stankovich, J. M., et al. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2007.12.019 · Cited by 264
Self-citationHowerton, C. L., Morgan, C. P., Fischer, D. B., & Bale, T. L. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1300065110 · Cited by 265
Human MAIT and CD8αα cells develop from a pool of type-17 precommitted CD8+ T cells
Walker, L. J., Kang, Y.-H., Smith, M. O., Tharmalingham, H., Ramamurthy, N., Fleming, V. M., Sahgal, N., Leslie, A. J., Oo, Y. H., Geremia, A., et al. (2011) · Blood · doi:10.1182/blood-2011-05-353789 · Cited by 261
Reynolds, N., Salmon‐Divon, M., Dvinge, H., Hynes-Allen, A. M., Balasooriya, G. I., Leaford, D., Behrens, A., Bertone, P., & Hendrich, B. (2011) · The EMBO Journal · doi:10.1038/emboj.2011.431 · Cited by 269
Gene Expression Atlas at the European Bioinformatics Institute
Kapushesky, M., Emam, I., Holloway, E., Kurnosov, P., Zorin, A., MALONE, J. M., Rustici, G., Williams, E. M., Parkinson, H., & Brāzma, A. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp936 · Cited by 254
Different TCR-induced T lymphocyte responses are potentiated by stiffness with variable sensitivity
Saitakis, M., Dogniaux, S., Goudot, C., Bufi, N., Asnacios, S., Maurin, M., Randriamampita, C., Asnacios, A., & Hivroz, C. (2017) · eLife · doi:10.7554/elife.23190 · Cited by 253
Immuno-genomic landscape of osteosarcoma
Wu, C.-C., Beird, H. C., Andrew Livingston, J., Advani, S., Mitra, A., Cao, S., Reuben, A., Ingram, D., Wang, W.-L., Ju, Z., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-14646-w · Cited by 251
Neto, J. B. D. A., Turchetto‐Zolet, A. C., de Oliveira, L. F. V., Zanettini, M. H. B., & Margis-Pinheiro, M. M. A. N. (2013) · FEBS Journal · doi:10.1111/febs.12159 · Cited by 250
Hall, E., Volkov, P., Dayeh, T., Esguerra, J. L. S., Salö, S., Eliasson, L., Rönn, T., Bacos, K., & Ling, C. (2014) · Genome Biology · doi:10.1186/s13059-014-0522-z · Cited by 249
Schoenfeld, J. D., Giobbie‐Hurder, A., Ranasinghe, S., Kao, K. Z., Lako, A., Tsuji, J., Liu, Y., Brennick, R. C., Gentzler, R. D., Lee, C. B., et al. (2021) · The Lancet Oncology · doi:10.1016/s1470-2045(21)00658-6 · Cited by 251
Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data
Alakwaa, F., Chaudhary, K., & Garmire, L. X. (2017) · Journal of Proteome Research · doi:10.1021/acs.jproteome.7b00595 · Cited by 251
Terlecki‐Ζaniewicz, L., Lämmermann, I., Latreille, J., Bobbili, M. R., Pils, V., Schosserer, M., Weinmüllner, R., Dellago, H., Skalicky, S., Pum, D., et al. (2018) · Aging · doi:10.18632/aging.101452 · Cited by 249
Patnaik, S. K., Kannisto, E. D., Knudsen, S., & Yendamuri, S. (2009) · Cancer Research · doi:10.1158/0008-5472.can-09-3153 · Cited by 246
Izquierdo-Useros, N., Lorizate, M., Puertas, M. C., Rodriguez-Plata, M. T., Zangger, N., Erikson, E., Pino, M., Erkizia, I., Glass, B., Clotet, B., et al. (2012) · PLoS Biology · doi:10.1371/journal.pbio.1001448 · Cited by 244
Sutherland, A. J., Thomas, M., Brandon, R. A., Brandon, R. B., Lipman, J., Tang, B. M. P., McLean, A. S., Pascoe, R., Price, G. R., Nguyen, T., et al. (2011) · Critical Care · doi:10.1186/cc10274 · Cited by 246
Venn diagrams in bioinformatics
Jia, A., Xu, L., & Wang, Y. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab108 · Cited by 249
Houtepen, L. C., Vinkers, C. H., Carrillo-Roa, T., Hiemstra, M., van Lier, P. A., Meeus, W., Branje, S., Heim, C. M., Nemeroff, C. B., Mill, J., et al. (2016) · Nature Communications · doi:10.1038/ncomms10967 · Cited by 242
Drug Target Prediction and Repositioning Using an Integrated Network-Based Approach
Emig, D., Ivliev, A. E., Pustovalova, O., Lancashire, L., Bureeva, S. V., Nikolsky, Y., & Bessarabova, M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0060618 · Cited by 242
Gene expression profiling in the adult Down syndrome brain
Lockstone, H. E., Harris, L. W., Swatton, J. E., Wayland, M. T., Holland, A. J., & Bahn, S. (2007) · Genomics · doi:10.1016/j.ygeno.2007.08.005 · Cited by 240
Metadata
- Authors
- Smyth, G. K.
- Corresponding author
- Smyth, G. K.
- ORCID
- Smyth, G. K.
- Venue
- Statistics for Biology and Health
- Publisher
- Springer-Verlag
- Published
- 2005-12-29
- Pages
- 397-420
- OpenAlex
- W1546952499
- Cited by
- 5,796
- References
- 9
- Citations by year
- 2026: 95 · 2025: 115 · 2024: 177 · 2023: 212 · 2022: 258 · 2021: 316 · 2020: 329 · 2019: 270 · 2018: 266 · 2017: 356 · 2016: 387 · 2015: 559 · 2014: 529 · 2013: 433 · 2012: 365
- FWCI
- 195.35
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Springer eBooks (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- limma, differential gene expression, microarray data, linear models, empirical Bayes, factorial design, time-course experiments, biological replication
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review