Quantitative Monitoring of Gene Expression Patterns with a Complementary DNA Microarray
Abstract
A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were used for quantitative expression measurements of the corresponding genes. Because of the small format and high density of the arrays, hybridization volumes of 2 microliters could be used that enabled detection of rare transcripts in probe mixtures derived from 2 micrograms of total cellular messenger RNA. Differential expression measurements of 45 Arabidopsis genes were made by means of simultaneous, two-color fluorescence hybridization.
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Particularly in the last 25 years, there has been an ever increasing number of ALE experiments with Escherichia coli and Saccharomyces cerevisiae being the most prominent organisms under investigation.
“however, particularly in the last 25 years, there has been an ever increasing number of such experiments with Escherichia coli and Saccharomyces cerevisiae being the most prominent organisms under investigation [26-28].”
From Adaptive laboratory evolution—Principles and applications for biotechnology (2013) · cites this paper as [27]
Cites
Kawasaki, E. S., Clark, S., Coyne, M. Y., Smith, S. D., Champlin, R. E., Witte, O. N., & McCormick, F. P. (1988) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.85.15.5698 · Cited by 701 · see citing works
Newman, T., de Bruijn, F. J., Green, P., Keegstra, K., Kende, H., McIntosh, L., Ohlrogge, J. B., Raikhel, N. V., Somerville, S. C., Thomashow, M. F., et al. (1994) · PLANT PHYSIOLOGY · doi:10.1104/pp.106.4.1241 · Cited by 623 · see citing works
Parameters of the human genome.
Morton, N. E. (1991) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.88.17.7474 · Cited by 519 · see citing works
Characterization of the genome of Arabidopsis thaliana
Pruitt, R. E., & Meyerowitz, E. M. (1986) · Journal of Molecular Biology · doi:10.1016/0022-2836(86)90226-3 · Cited by 269 · see citing works
HD-Zip proteins: members of an Arabidopsis homeodomain protein superfamily.
Schena, M., & Davis, R. W. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.9.3894 · Cited by 256 · see citing works
Self-citationArabidopsis thaliana and Plant Molecular Genetics
Meyerowitz, E. M., & Pruitt, R. E. (1985) · Science · doi:10.1126/science.229.4719.1214 · Cited by 253 · see citing works
Höfte, H., Desprez, T., Amselem, J., Chiapello, H., Caboche, M. M., Moisan, A., Jourjon, M.-F., Charpenteau, J. L., Berthomieu, P., Guerrier, D., et al. (1993) · The Plant Journal · doi:10.1046/j.1365-313x.1993.04061051.x · Cited by 231 · see citing works
Mapping the whole human genome by fingerprinting yeast artificial chromosomes
Bellanné‐Chantelot, C., Lacroix, B., Ougen, P., Billault, A., Beaufils, S., Bertrand, S., Georges, I., Glibert, F., Gros, I., Lucotte, G., et al. (1992) · Cell · doi:10.1016/0092-8674(92)90254-a · Cited by 159 · see citing works
The HAT4 gene of Arabidopsis encodes a developmental regulator.Preprint
Schena, M., Lloyd, A., & Davis, R. W. (1993) · Genes & Development · doi:10.1101/gad.7.3.367 · Cited by 135 · see citing works
Self-citationStructure of homeobox-leucine zipper genes suggests a model for the evolution of gene families.
Schena, M., & Davis, R. W. (1994) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.91.18.8393 · Cited by 79 · see citing works
Self-citationIdentification and map position of YAC clones comprising one‐third of the Arabidopsis genome.
Hwang, I., Kohchi, T., Bm, H., et al. (1991) · The Plant Journal · doi:10.1046/j.1365-313x.1991.t01-5-00999.x · Cited by 67 · see citing works
Jarvis, P., Lister, C., Szabó, V. M., & Dean, C. (1994) · Plant Molecular Biology · doi:10.1007/bf00023565 · Cited by 63 · see citing works
The human genome project. Prospects and implications for clinical medicine
Green, E. D. (1991) · JAMA · doi:10.1001/jama.266.14.1966 · Cited by 37 · see citing works
Assessing Mapping Progress in the Human Genome Project
Cox, D. R., Green, E. D., Lander, E. S., et al. (1994) · Science · doi:10.1126/science.8091223 · Cited by 35 · see citing works
Gene density and organization in a small region of the Arabidopsis thaliana genome
Guen, L. L., Thomas, M., & Kreis, M. E. (1994) · Molecular and General Genetics MGG · doi:10.1007/bf00290120 · Cited by 34 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Subramanian, A., Tamayo, P., Mootha, V. K., Mukherjee, S., Ebert, B. L., Gillette, M. A., Paulovich, A., Pomeroy, S. L., Golub, T. R., Lander, E. S., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0506580102 · Cited by 53,625 · see citing works
Vandesompele, J., De Preter, K., Pattyn, F., Poppe, B., Van Roy, N., De Paepe, A., & Speleman, F. (2002) · Genome Biology · doi:10.1186/gb-2002-3-7-research0034 · Cited by 20,038 · see citing works
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository
Edgar, R. (2002) · Nucleic Acids Research · doi:10.1093/nar/30.1.207 · Cited by 13,288 · see citing works
Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling
Alizadeh, A. A., Eisen, M. B., Davis, R. E., Ma, C., Lossos, I. S., Rosenwald, A., Boldrick, J. C., Sabet, H., Tran, T., Yu, X., et al. (2000) · Nature · doi:10.1038/35000501 · Cited by 9,925 · see citing works
Self-citationFrom molecular to modular cell biology.
Hartwell, L. H., Hopfield, J. J., Leibler, S., & Murray, A. W. (1999) · Nature · doi:10.1038/35011540 · Cited by 3,632 · see citing works
Designing materials for biology and medicine
Langer, R., & Tirrell, D. A. (2004) · Nature · doi:10.1038/nature02388 · Cited by 3,198 · see citing works
Printing Proteins as Microarrays for High-Throughput Function Determination
MacBeath, G., & Schreiber, S. L. (2000) · Science · doi:10.1126/science.289.5485.1760 · Cited by 2,767 · see citing works
A N <scp>EW</scp> A <scp>PPROACH TO</scp> D <scp>ECODING</scp> L <scp>IFE</scp> : Systems Biology
Ideker, T., Galitski, T., & Hood, L. (2001) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev.genom.2.1.343 · Cited by 1,664 · see citing works
The microglial sensome revealed by direct RNA sequencing
Hickman, S. E., Kingery, N. D., Ohsumi, T. K., Borowsky, M. L., Wang, L.-C., Means, T. K., & El Khoury, J. (2013) · Nature Neuroscience · doi:10.1038/nn.3554 · Cited by 1,511 · see citing works
Molecular characterization of the tumor microenvironment in breast cancer
Allinen, M., Beroukhim, R., Cai, L., Brennan, C., Lahti-Domenici, J., Huang, H., Porter, D., Hu, M., Chin, L., Richardson, A., et al. (2004) · Cancer Cell · doi:10.1016/j.ccr.2004.06.010 · Cited by 1,299 · see citing works
Transcriptome Engineering with RNA-Targeting Type VI-D CRISPR Effectors
Konermann, S., Lotfy, P., Brideau, N. J., Oki, J., Shokhirev, M. N., & Hsu, P. D. (2018) · Cell · doi:10.1016/j.cell.2018.02.033 · Cited by 1,164 · see citing works
The New Genomics: Global Views of Biology
Lander, E. S. (1996) · Science · doi:10.1126/science.274.5287.536 · Cited by 1,174 · see citing works
Counting absolute numbers of molecules using unique molecular identifiers
Kivioja, T., Vähärautio, A., Karlsson, K., Bonke, M., Enge, M., Linnarsson, S., & Taipale, J. (2012) · Nature Methods · doi:10.1038/nmeth.1778 · Cited by 1,010 · see citing works
Proteomics by Mass Spectrometry: Approaches, Advances, and Applications
Yates, J. R., Ruse, C. I., & Nakorchevsky, A. (2009) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-061008-124934 · Cited by 1,078 · see citing works
Computational methods for transcriptome annotation and quantification using RNA-seq
Garber, M., Grabherr, M. G., Guttman, M., & Trapnell, C. (2011) · Nature Methods · doi:10.1038/nmeth.1613 · Cited by 1,042 · see citing works
Prebiotic Systems Chemistry: New Perspectives for the Origins of Life
Ruiz-Mirazo, K., Briones, C., & de la Escosura, A. (2014) · Chemical Reviews · doi:10.1021/cr2004844 · Cited by 930 · see citing works
Kukurba, K. R., & Montgomery, S. B. (2015) · Cold Spring Harbor Protocols · doi:10.1101/pdb.top084970 · Cited by 924 · see citing works
Mutant PIK3CA promotes cell growth and invasion of human cancer cells.
Samuels, Y., Diaz, L. A., Schmidt-Kittler, O., Cummins, J. M., DeLong, L., Cheong, I., Rago, C., Huso, D. L., Lengauer, C., Kinzler, K. W., et al. (2005) · Cancer Cell · doi:10.1016/j.ccr.2005.05.014 · Cited by 915 · see citing works
Courcelle, J., Khodursky, A., Peter, B., Brown, P. O., & Hanawalt, P. C. (2001) · Genetics · doi:10.1093/genetics/158.1.41 · Cited by 853 · see citing works
Self-citationThe mutual information: detecting and evaluating dependencies between variables
Steuer, R., Kurths, J., Daub, C. O., Weise, J., & Selbig, J. (2002) · Bioinformatics · doi:10.1093/bioinformatics/18.suppl_2.s231 · Cited by 815 · see citing works
Adaptive laboratory evolution—Principles and applications for biotechnology
Dragosits, M., & Mattanovich, D. (2013) · Microbial Cell Factories · doi:10.1186/1475-2859-12-64 · Cited by 827 · see citing works
An Abundance of Ubiquitously Expressed Genes Revealed by Tissue Transcriptome Sequence Data
Ramsköld, D., Wang, E. T., Burge, C. B., & Sandberg, R. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000598 · Cited by 820 · see citing works
Massive mining of publicly available RNA-seq data from human and mouse
Lachmann, A., Torre, D., Keenan, A. B., Jagodnik, K. M., Lee, H. J., Wang, L., Silverstein, M. C., & Ma’ayan, A. (2018) · Nature Communications · doi:10.1038/s41467-018-03751-6 · Cited by 701 · see citing works
Nanoliter-scale synthesis of arrayed biomaterials and application to human embryonic stem cells
Anderson, D. G., Levenberg, S., & Langer, R. (2004) · Nature Biotechnology · doi:10.1038/nbt981 · Cited by 747 · see citing works
Reliability and reproducibility issues in DNA microarray measurements
DRAGHICI, S., KHATRI, P., EKLUND, A., & SZALLASI, Z. (2006) · Trends in Genetics · doi:10.1016/j.tig.2005.12.005 · Cited by 590 · see citing works
Hebert, A. S., Richards, A. L., Bailey, D. J., Ulbrich, A., Coughlin, E. E., Westphall, M. S., & Coon, J. J. (2014) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m113.034769 · Cited by 528 · see citing works
“Owing to cost, speed, and accessibility, transcriptomic analysis is often used as a proteomic proxy (3, 4).”
MethodSingle-Cell Gene Expression Profiling
Levsky, J. M., Shenoy, S. M., Pezo, R. C., & Singer, R. H. (2002) · Science · doi:10.1126/science.1072241 · Cited by 526 · see citing works
Predictive Behavior Within Microbial Genetic Networks
Tagkopoulos, I., Liu, Y.-C., & Tavazoie, S. (2008) · Science · doi:10.1126/science.1154456 · Cited by 519 · see citing works
Protein Microarrays for Gene Expression and Antibody Screening
Lueking, A., Horn, M., Eickhoff, H., Büssow, K., Lehrach, H., & Walter, G. (1999) · Analytical Biochemistry · doi:10.1006/abio.1999.4063 · Cited by 433 · see citing works
A Systems Level Analysis of Transcriptional Changes in Alzheimer's Disease and Normal Aging
Miller, J. A., Oldham, M. C., & Geschwind, D. H. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.4098-07.2008 · Cited by 385 · see citing works
The External RNA Controls Consortium: a progress report
The External RNA Controls Consortium (2005) · Nature Methods · doi:10.1038/nmeth1005-731 · Cited by 373 · see citing works
Reverse engineering cellular networks
Margolin, A. A., Wang, K., Lim, W. K., Kustagi, M., Nemenman, I., & Califano, A. (2006) · Nature Protocols · doi:10.1038/nprot.2006.106 · Cited by 379 · see citing works
Sequeira, A., Mamdani, F., Ernst, C., Vawter, M. P., Bunney, W. E., Lebel, V., Rehal, S., Klempan, T., Gratton, A., Benkelfat, C., et al. (2009) · PLoS ONE · doi:10.1371/journal.pone.0006585 · Cited by 388 · see citing works
Statistical Design and Analysis of RNA Sequencing Data
Auer, P. L., & Doerge, R. W. (2010) · Genetics · doi:10.1534/genetics.110.114983 · Cited by 393 · see citing works
Ishida, N., Hayashi, K., Hoshijima, M., Ogawa, T., Koga, S., Miyatake, Y., Kumegawa, M., Kimura, T., & Takeya, T. (2002) · Journal of Biological Chemistry · doi:10.1074/jbc.m205063200 · Cited by 377 · see citing works
A practical guide to the oral microbiome and its relation to health and disease
Krishnan, K., Chen, T., & Paster, B. (2017) · Oral Diseases · doi:10.1111/odi.12509 · Cited by 347 · see citing works
“DNA microarrays used signals from hybridization of DNA fragments to hundreds or thousands of complementary probes arrayed on a glass slide for expression profiling (Schena et al., 1995).”
MethodIn silico method for modelling metabolism and gene product expression at genome scale
Lerman, J. A., Hyduke, D. R., Latif, H., Portnoy, V. A., Lewis, N. E., Orth, J. D., Schrimpe-Rutledge, A. C., Smith, R. D., Adkins, J. N., Zengler, K., et al. (2012) · Nature Communications · doi:10.1038/ncomms1928 · Cited by 266 · see citing works
Devarajan, P., Mishra, J., Supavekin, S., Patterson, L. T., & Steven Potter, S. (2003) · Molecular Genetics and Metabolism · doi:10.1016/j.ymgme.2003.09.012 · Cited by 229 · see citing works
A comparison of gene set analysis methods in terms of sensitivity, prioritization and specificity
Tarca, A. L., Bhatti, G., & Romero, R. (2013) · PLoS ONE · doi:10.1371/journal.pone.0079217 · Cited by 203 · see citing works
Cheadle, C., Fan, J., Cho-Chung, Y. S., Werner, T., Ray, J., Do, L., Gorospe, M., & Becker, K. G. (2005) · BMC Genomics · doi:10.1186/1471-2164-6-75 · Cited by 183 · see citing works
Role of Hyphal Formation in Interactions of <i>Candida albicans</i> with Endothelial Cells
Phan, Q. T., Belanger, P. H., & Filler, S. G. (2000) · Infection and Immunity · doi:10.1128/iai.68.6.3485-3490.2000 · Cited by 181 · see citing works
Schwaller, B., Tetko, I. V., Tandon, P., Silveira, D. C., Vreugdenhil, M., Henzi, T., Potier, M.-C., Celio, M. R., & Villa, A. E. P. (2004) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2003.12.006 · Cited by 169 · see citing works
Kuo, M. D., Gollub, J., Sirlin, C. B., Ooi, C., & Chen, X. (2007) · Journal of Vascular and Interventional Radiology · doi:10.1016/j.jvir.2007.04.031 · Cited by 168 · see citing works
Li, J. Y., Boado, R. J., & Pardridge, W. M. (2001) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1097/00004647-200101000-00008 · Cited by 164 · see citing works
Polony gels enable amplifiable DNA stamping and spatial transcriptomics of chronic pain
Fu, X., Sun, L., Dong, R., Chen, J. Y., Silakit, R., Condon, L. F., Lin, Y., Lin, S., Palmiter, R. D., & Gu, L. (2022) · Cell · doi:10.1016/j.cell.2022.10.021 · Cited by 161 · see citing works
Progress in the use of microarray technology to study the neurobiology of disease
Mirnics, K., & Pevsner, J. (2004) · Nature Neuroscience · doi:10.1038/nn1230 · Cited by 150 · see citing works
Avoiding common pitfalls in machine learning omic data science
Teschendorff, A. E. (2019) · Nature Materials · doi:10.1038/s41563-018-0241-z · Cited by 132 · see citing works
Toxicity of anionic detergents determined by Saccharomyces cerevisiae microarray analysis
Sirisattha, S., Momose, Y., Kitagawa, E., & Iwahashi, H. (2004) · Water Research · doi:10.1016/j.watres.2003.08.027 · Cited by 130 · see citing works
Human transcriptome array for high-throughput clinical studies
Xu, W., Seok, J., Mindrinos, M. N., Schweitzer, A. C., Jiang, H., Wilhelmy, J., Clark, T. A., Kapur, K., Xing, Y., Faham, M., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1019753108 · Cited by 124 · see citing works
Self-citationElectrochemically directed synthesis of oligonucleotides for DNA microarray fabrication
Egeland, R. D. (2005) · Nucleic Acids Research · doi:10.1093/nar/gni117 · Cited by 122 · see citing works
Fine, B. M., Kaspers, G. J. L., Ho, M., Loonen, A. H., & Boxer, L. M. (2005) · Cancer Research · doi:10.1158/0008-5472.291.65.1 · Cited by 103 · see citing works
Simpson, J. L., Bischoff, F. Z., Kamat, A., Buster, J. E., & Carson, S. A. (2003) · Obstetrics and Gynecology Clinics of North America · doi:10.1016/s0889-8545(02)00051-7 · Cited by 83 · see citing works
Evaluating the Impact of Sequencing Depth on Transcriptome Profiling in Human Adipose
Liu, Y., Ferguson, J. F., Xue, C., Silverman, I. M., Gregory, B., Reilly, M. P., & Li, M. (2013) · PLoS ONE · doi:10.1371/journal.pone.0066883 · Cited by 74 · see citing works
Calarco, J. A., Zhen, M., & Blencowe, B. J. (2011) · RNA · doi:10.1261/rna.2603911 · Cited by 72 · see citing works
Huddleston, H. G., Wong, K.-K., Welch, W. R., Berkowitz, R. S., & Mok, S. C. (2005) · Gynecologic Oncology · doi:10.1016/j.ygyno.2004.08.047 · Cited by 68 · see citing works
Rat Blood–Brain Barrier Genomics. II
Li, J. Y., Boado, R. J., & Pardridge, W. M. (2002) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1097/01.wcb.0000040944.89393.0f · Cited by 46 · see citing works
Digital expression profiles of the prostate androgen-response program
Clegg, N., Eroglu, B., Ferguson, C., Arnold, H., Moorman, A., & Nelson, P. S. (2002) · The Journal of Steroid Biochemistry and Molecular Biology · doi:10.1016/s0960-0760(01)00167-4 · Cited by 37 · see citing works
Kawai, T., Morita, K., Masuda, K., Nishida, K., Shikishima, M., Ohta, M., Saito, T., & Rokutan, K. (2007) · Biological Psychology · doi:10.1016/j.biopsycho.2007.07.008 · Cited by 36 · see citing works
Transcriptional responses to DNA damage
Silva, E., & Ideker, T. (2019) · DNA repair · doi:10.1016/j.dnarep.2019.05.002 · Cited by 31 · see citing works
Representing high throughput expression profiles via perturbation barcodes reveals compound targets
Filzen, T. M., Kutchukian, P. S., Hermes, J. D., Li, J., & Tudor, M. (2017) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1005335 · Cited by 31 · see citing works
Advancing insights into stem cell niche complexities with next-generation technologies
Heitman, N., Saxena, N., & Rendl, M. (2018) · Current Opinion in Cell Biology · doi:10.1016/j.ceb.2018.06.012 · Cited by 31 · see citing works
PECA: A Novel Statistical Tool for Deconvoluting Time-Dependent Gene Expression Regulation
Teo, G., Vogel, C., Ghosh, D., Kim, S., & Choi, H. (2014) · Journal of Proteome Research · doi:10.1021/pr400855q · Cited by 30 · see citing works
van Dijk, J. P., Cankar, K., Hendriksen, P. J. M., Beenen, H. G., Zhu, M., Scheffer, S., Shepherd, L. V. T., Stewart, D., Davies, H. V., Leifert, C., et al. (2012) · Journal of Agricultural and Food Chemistry · doi:10.1021/jf204696w · Cited by 26 · see citing works
Durruthy-Durruthy, R., Gottlieb, A., & Heller, S. (2015) · Nature Protocols · doi:10.1038/nprot.2015.022 · Cited by 20 · see citing works
Expression profiling of drug response - from genes to pathways
Herwig, R., & Lehrach, H. (2006) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2006.8.3/rherwig · Cited by 14 · see citing works
Yu, H., Nguyen, K., Royce, T., Qian, J., Nelson, K., Snyder, M., & Gerstein, M. (2006) · Nucleic Acids Research · doi:10.1093/nar/gkl871 · Cited by 13 · see citing works
The impact of quantitative optimization of hybridization conditions on gene expression analysis
Sykacek, P., Kreil, D. P., Meadows, L. A., Auburn, R. P., Fischer, B., Russell, S., & Micklem, G. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-73 · Cited by 13 · see citing works
Technology Insight: querying the genome with microarrays—progress and hope for neurological disease
Coppola, G., & Geschwind, D. H. (2006) · Nature Clinical Practice Neurology · doi:10.1038/ncpneuro0133 · Cited by 12 · see citing works
Correcting positional correlations in Affymetrix® Genome Chips
Homouz, D., Chen, G., & Kudlicki, A. S. (2015) · Scientific Reports · doi:10.1038/srep09078 · Cited by 4 · see citing works
Fundamental Methods in Molecular Biology
Ijaz, S., & Hassan, S. (2026) · Molecular Biology Methods · doi:10.1007/978-981-92-2642-9_1
- Authors
- Schena, M., Shalon, D., Davis, R. W., & Brown, P. O.
- Affiliations
- Stanford Medicine (US)
- Corresponding author
- Schena, Mark
- Shalon, Dari
- Davis, Ronald W.
- Brown, Patrick O.
- Venue
- Science
- Published
- 1995-10-20
- Volume
- 270
- Issue
- 5235
- Pages
- 467-470
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W1970156673
- Cited by
- 9,609
- References
- 15
- Citations by year
- 2026: 68 · 2025: 89 · 2024: 117 · 2023: 91 · 2022: 109 · 2021: 137 · 2020: 140 · 2019: 168 · 2018: 193 · 2017: 196 · 2016: 214 · 2015: 269 · 2014: 312 · 2013: 328 · 2012: 418
- FWCI
- 29.38
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r21hg000450-02)
- National Institute on Aging (R37AG00198)
- National Human Genome Research Institute (R21HG00450)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Advanced Biosensing Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
- Keywords
- gene expression profiling, differential gene expression, Arabidopsis thaliana, mRNA
- MeSH terms
- DNA-Binding Proteins, Genetic Techniques, Humans, Molecular Sequence Data, Nucleic Acid Hybridization, RNA, Messenger, Transcription Factors, RNA Probes, Gene Expression, Genome, Human, Polymerase Chain Reaction, Genes, Plant, Arabidopsis, DNA, Complementary, Homeodomain Proteins, Plant Leaves, Plant Roots, DNA, Plant, RNA, Plant, Arabidopsis Proteins, Plants, Genetically Modified
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