Academic literature on the topic 'CDNA microarray'

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Journal articles on the topic "CDNA microarray"

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Handley, Daniel, Nicoleta Serban, David G. Peters, and Clark Glymour. "Concerns About Unreliable Data from Spotted cDNA Microarrays Due to Cross-Hybridization and Sequence Errors." Statistical Applications in Genetics and Molecular Biology 3, no. 1 (2004): 1–2. http://dx.doi.org/10.2202/1544-6115.1091.

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We discuss our concerns regarding the reliability of data generated by spotted cDNA microarrays. Two types of error we highlight are cross-hybridization artifact due to sequence homologies and sequence errors in the cDNA used for spotting on microarrays. We feel that statisticians who analyze microarray data should be aware of these sources of unreliability intrinsic to cDNA microarray design and use.
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Pérez-Enciso, Miguel, Miguel A. Toro, Michel Tenenhaus, and Daniel Gianola. "Combining Gene Expression and Molecular Marker Information for Mapping Complex Trait Genes: A Simulation Study." Genetics 164, no. 4 (2003): 1597–606. http://dx.doi.org/10.1093/genetics/164.4.1597.

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Abstract A method for mapping complex trait genes using cDNA microarray and molecular marker data jointly is presented and illustrated via simulation. We introduce a novel approach for simulating phenotypes and genotypes conditionally on real, publicly available, microarray data. The model assumes an underlying continuous latent variable (liability) related to some measured cDNA expression levels. Partial least-squares logistic regression is used to estimate the liability under several scenarios where the level of gene interaction, the gene effect, and the number of cDNA levels affecting liabi
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Wang, Zidong, Bachar Zineddin, Jinling Liang, et al. "cDNA microarray adaptive segmentation." Neurocomputing 142 (October 2014): 408–18. http://dx.doi.org/10.1016/j.neucom.2014.03.052.

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Liang, Mingyu, Amy G. Briggs, Elizabeth Rute, Andrew S. Greene, and Allen W. Cowley. "Quantitative assessment of the importance of dye switching and biological replication in cDNA microarray studies." Physiological Genomics 14, no. 3 (2003): 199–207. http://dx.doi.org/10.1152/physiolgenomics.00143.2002.

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Dye switching and biological replication substantially increase the cost and the complexity of cDNA microarray studies. The objective of the present analysis was to quantitatively assess the importance of these procedures to provide a quantitative basis for decision-making in the design of microarray experiments. Taking advantage of the unique characteristics of a published data set, the impact of these procedures on the reliability of microarray results was calculated. Adding a second microarray with dye switching substantially increased the correlation coefficient between observed and predic
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Yang, Y. H. "Analysis of cDNA microarray images." Briefings in Bioinformatics 2, no. 4 (2001): 341–49. http://dx.doi.org/10.1093/bib/2.4.341.

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Emi, Mitsuru. "cDNA Microarray and SNP Analysis." Journal of Nippon Medical School 68, no. 5 (2001): 411–12. http://dx.doi.org/10.1272/jnms.68.411.

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Smyth, Gordon K., and Terry Speed. "Normalization of cDNA microarray data." Methods 31, no. 4 (2003): 265–73. http://dx.doi.org/10.1016/s1046-2023(03)00155-5.

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Mizukami, Satomi, Yoshiteru Suzuki, Emiko Kitagawa, and Hitoshi Iwahashi. "Standardization of cDNA microarray technology for toxicogenomics; essential data for initiating cDNA microarray studies." Chem-Bio Informatics Journal 4, no. 2 (2004): 38–55. http://dx.doi.org/10.1273/cbij.4.38.

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LEE, PHILIP R., JONATHAN E. COHEN, ELISABETTA A. TENDI, et al. "Transcriptional profiling in an MPNST-derived cell line and normal human Schwann cells." Neuron Glia Biology 1, no. 2 (2004): 135–47. http://dx.doi.org/10.1017/s1740925x04000274.

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cDNA microarrays were utilized to identify abnormally expressed genes in a malignant peripheral nerve sheath tumor (MPNST)-derived cell line, T265, by comparing the mRNA abundance profiles with that of normal human Schwann cells (nhSCs). The findings characterize the molecular phenotype of this important cell-line model of MPNSTs, and elucidate the contribution of Schwann cells in MPNSTs. In total, 4608 cDNA sequences were screened and hybridizations replicated on custom cDNA microarrays. In order to verify the microarray data, a large selection of differentially expressed mRNA transcripts wer
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Nobis, William, Xiaoning Ren, Steven P. Suchyta, Thomas R. Suchyta, Adroaldo J. Zanella, and Paul M. Coussens. "Development of a porcine brain cDNA library, EST database, and microarray resource." Physiological Genomics 16, no. 1 (2003): 153–59. http://dx.doi.org/10.1152/physiolgenomics.00099.2003.

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Recent developments in expressed sequence tag (EST) and cDNA microarray technology have had a dramatic impact on the ability of scientists to study responses of thousands of genes to internal and external stimuli. In neurobiology, studies of the human brain have been expanding rapidly by use of functional genomics techniques. To enhance these studies and allow use of a porcine brain model, a normalized porcine brain cDNA library (PBL) has been generated and used as a base for EST discovery and microarray generation. In this report, we discuss initial sequence analysis of 965 clones from this r
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Dissertations / Theses on the topic "CDNA microarray"

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Fraser, Karl. "cDNA microarray image analysis : a fully automated framework." Thesis, Brunel University, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.429240.

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Stanzel, Sven. "Optimale statistische Versuchsplanung dreifaktorieller Zwei-Farben-cDNA-Microarray-Experimente /." Dortmund, 2008. http://opac.nebis.ch/cgi-bin/showAbstract.pl?sys=000254108.

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Soneji, Sharnit. "Statistical Analysis of cDNA Microarray Directed by Gene Function." Thesis, Birkbeck (University of London), 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.487759.

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Microarrays allow the expression level of thousands of genes to be measured simultaneously. This study will address analytical issues predominantly concerned with eDNA arrays. These include normalisation and data preprocessing, leading to an assessment of cluster analysis and the integration of database information to elucidate functional classes of biological relevance. This is then extended further to classify genes of unknown function using Markov Random Fields. I Modelling of uneven surface trends were considered in a new 2D-normalisation method which outperformed the popular loess method
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Jouenne, Vincent Y. "Critical Issues in the Processing of cDNA Microarray Images." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/33960.

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Microarray technology enables simultaneous gene expression level monitoring for thousands of genes. While this technology has now been recognized as a powerful and cost-effective tool for large-scale analysis, the many systematic sources of experimental variations introduce inherent errors in the extracted data. Data is gathered by processing scanned images of microarray slides. Therefore robust image processing is particularly important and has a large impact on downstream analysis. The processing of the scanned images can be subdivided in three phases: gridding, segmentation and data extract
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Wu, Meng. "Data mining cDNA microarray experiment with a GEE approach /." Electronic version (PDF), 2004. http://dl.uncw.edu/etd/2004/wum/mengwu.pdf.

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Hintze, Eric Poole. "Small sample multiple testing with application to cDNA microarray data." Texas A&M University, 2005. http://hdl.handle.net/1969.1/4319.

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Many tests have been developed for comparing means in a two-sample scenario. Microarray experiments lead to thousands of such comparisons in a single study. Several multiple testing procedures are available to control experiment-wise error or the false discovery rate. In this dissertation, individual two-sample tests are compared based on accuracy, correctness, and power. Four multiple testing procedures are compared via simulation, based on data from the lab of Dr. Rajesh Miranda. The effect of sample size on power is also carefully examined. The two sample t-test followed by the Benjamini an
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Vesterlund, Jacob. "Feature Selection and Classification of cDNA Microarray Samples in ROSETTA." Thesis, Uppsala University, Department of Information Technology, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-88731.

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<p>The advent of cDNA microarray technology makes it possible to measure theexpression level of thousands of genes simultaneously. This creates large volumes of data that require computational analysis.</p><p>One application of microarray technology is cancer studies, where supervised learning may be used on microarray data to predicting tumour subtypes and other clinical parameters. The number of available objects (microarrays) is much smaller than the number of attributes (genes). Hence it is necessary to determine which attributes are important for predicting a parameter. Feature selection
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Zhu, Ximin. "Topics on statistical design and analysis of cDNA microarray experiment." Thesis, University of Glasgow, 2009. http://theses.gla.ac.uk/1206/.

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A microarray is a powerful tool for surveying the expression levels of many thousands of genes simultaneously. It belongs to the new genomics technologies which have important applications in the biological, agricultural and pharmaceutical sciences. In this thesis, we focus on the dual channel cDNA microarray which is one of the most popular microarray technologies and discuss three different topics: optimal experimental design; estimating the true proportion of true nulls, local false discovery rate (lFDR) and positive false discovery rate (pFDR) and dye effect normalization. The first topic
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Zhao, Hongya. "Statistical analysis of gene expression data in cDNA microarray experiments." HKBU Institutional Repository, 2006. http://repository.hkbu.edu.hk/etd_ra/657.

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Kan, Takatsugu. "Gene expression profiling in human esophageal cancers using cDNA microarray." Kyoto University, 2003. http://hdl.handle.net/2433/148738.

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Books on the topic "CDNA microarray"

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Maziarz, Marlena. Spotting error in cDNA microarray data. National Library of Canada, 2003.

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Howell, Brandon George. Gene expression profiling of UV-induced skin cancer using cDNA microarray technology. National Library of Canada, 2001.

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Rintala, Nina. Differential gene expression in radiosensitive and radioresistant breast cancer cells using cDNA microarray analysis. Laurentian University, 2001.

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Liao, Wei-Yen Perry. Characterization of an HNF-3[beta] inducible construct and a cDNA microarray screen for HNF-3[beta] targets. National Library of Canada, 2003.

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Cerullo, Dante. Identification of a novel diagnostic marker for viral myocarditis using cDNA microarrays. National Library of Canada, 2003.

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Handley, Heather Martin. Zebrafish cardiovascular cDNA microarrays: Expression profiling and gene discovery in embryos exposed to 2,3,7,8-Tetrachlorodibenzo-P-dioxin. Massachusetts Institute of Technology, 2003.

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Book chapters on the topic "CDNA microarray"

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Mousses, Spyro. "Microarray (cDNA) Technology." In Encyclopedia of Cancer. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-27841-9_3710-3.

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Mousses, Spyro. "Microarray (cDNA) Technology." In Encyclopedia of Cancer. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-46875-3_3710.

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Mousses, Spyro. "Microarray (cDNA) Technology." In Encyclopedia of Cancer. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-16483-5_3710.

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Rantala-Ylinen, Anne, Kaarina Sivonen, Annick Wilmotte, Hans C. P. Matthijs, and J. Merijn Schuurmans. "DNA (Diagnostic) and cDNA Microarray." In Molecular Tools for the Detection and Quantification of Toxigenic Cyanobacteria. John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119332169.ch8.

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Bilke, Sven, and Javed Khan. "Analysis of Comparative Genomic Hybridization Data on cDNA Microarrays." In Microarray Data Analysis. Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-390-5_11.

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Larese, Mónica G., and Juan Carlos Gómez. "Quantitative Improvements in cDNA Microarray Spot Segmentation." In Advances in Bioinformatics and Computational Biology. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03223-3_6.

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Wong, Kwong-Kwok, Jun Kanno, Rita Cheng, et al. "Application of cDNA microarray for uterotrophic assay." In Toxicogenomics. Springer Japan, 2003. http://dx.doi.org/10.1007/978-4-431-66999-9_18.

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Yang, Yee Hwa, and Natalie P. Thorne. "Normalization for two-color cDNA microarray data." In Institute of Mathematical Statistics Lecture Notes - Monograph Series. Institute of Mathematical Statistics, 2003. http://dx.doi.org/10.1214/lnms/1215091155.

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Laere, Steven J. Van, Peter B. Vermeulen, and Luc Y. Dirix. "cDNA Microarray Analysis of Inflammatory Breast Cancer Signatures." In Methods in Molecular Biology™. Humana Press, 2009. http://dx.doi.org/10.1007/978-1-60327-530-9_6.

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Weng, Guirong, Yijun Hu, and Zhiyao Li. "cDNA Microarray Image Filtering Using Shape-Adaptive DCT." In Recent Advances in Computer Science and Information Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25792-6_17.

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Conference papers on the topic "CDNA microarray"

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Caffrey, S. M., H. s. Park, G. Voordouw, and Jenny Been. "Gene Array Analysis of Sulfate-Reducing Bacteria Grown on an Iron Electrode under Conditions of Cathodic Protection." In CORROSION 2008. NACE International, 2008. https://doi.org/10.5006/c2008-08653.

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Abstract Sulfate-reducing bacteria (SRB) can contribute to microbially-influenced corrosion (MIC) of iron. Removal of hydrogen formed at the metal surface is often regarded as a critical step in the progression of MIC. Hence SRB-mediated iron corrosion and hydrogen oxidation may be comparable processes. Because the genome sequence of the model SRB Desulfovibrio vulgaris Hildenborough (DvH) is now known, this theory can be tested by genomics technologies. D. vulgaris has four periplasmic hydrogenases to oxidize molecular hydrogen, one iron-only (Hyd), two nickel-iron (Hyn1 and Hyn2) and one nic
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Tozduman, Ersin, and Songul Albayrak. "cDNA microarray image analysis." In 2009 14th National Biomedical Engineering Meeting. IEEE, 2009. http://dx.doi.org/10.1109/biyomut.2009.5130308.

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Liew, Alan Wee-Chung, Hong Yan, Tuan D. Pham, and Xiaobo Zhou. "Automated cDNA Microarray Image Segmentation." In COMPUTATIONAL MODELS FOR LIFE SCIENCES/CMLS '07. AIP, 2007. http://dx.doi.org/10.1063/1.2816637.

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Pan, Youlian, Jitao Zou, Yi Huang, Ziying Liu, Sieu Phan, and Fazel A. Famili. "Goal Driven Analysis of cDNA Microarray Data." In 2009 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB). IEEE, 2009. http://dx.doi.org/10.1109/cibcb.2009.4925727.

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Chan, Shih-Huang, Wan-Chi Chang, and Chien-Ju Lin. "Contamination removal methods in cDNA microarray data." In 2006 IEEE International Workshop on Genomic Signal Processing and Statistics. IEEE, 2006. http://dx.doi.org/10.1109/gensips.2006.353145.

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Kaabouch, Naima, and Hamid Shahbazkia. "Automatic techniques for gridding CDNA microarray images." In 2008 IEEE International Conference on Electro/Information Technology (EIT 2008). IEEE, 2008. http://dx.doi.org/10.1109/eit.2008.4554300.

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Lukac, Rastislav, and Konstantinos Plataniotis. "cDNA Microarray Imaging using Single-Sensor Technology." In 2006 Canadian Conference on Electrical and Computer Engineering. IEEE, 2006. http://dx.doi.org/10.1109/ccece.2006.277841.

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Yao, Zhang, and Wu Shunxiang. "Statistsics-Adaptive Method for cDNA Microarray Images Gridding." In 2012 4th International Conference on Digital Home (ICDH). IEEE, 2012. http://dx.doi.org/10.1109/icdh.2012.52.

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Uslan, V., and İ Ö Bucak. "Clustering-based spot segmentation of cDNA microarray images." In 2010 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC 2010). IEEE, 2010. http://dx.doi.org/10.1109/iembs.2010.5626430.

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Weng, Guirong, Yuehuan Wang, and Jian Su. "cDNA Microarray Image Processing Using Spot Centroid of Intensity." In 2008 International Conference on Computational Intelligence and Security (CIS). IEEE, 2008. http://dx.doi.org/10.1109/cis.2008.31.

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Reports on the topic "CDNA microarray"

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Jornsten, Rebeka, Bin Yu, Wei Wang, and Kannan Ramchandran. Compression of cDNA and Inkjet Microarray Images. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada407645.

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Rosa, Artur J. M., Gang Ren, and James M. Reecy. Development of the BoviAnalyser cDNA Bovine Microarray. Iowa State University, 2004. http://dx.doi.org/10.31274/ans_air-180814-592.

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Gottardo, Raphael, Adrian E. Raftery, Ka Yee Yeung, and Roger E. Bumgarner. Robust Estimation of cDNA Microarray Intensities with Replicates. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada459797.

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ทัศนาขจร, อัญชลี, สิริพร พงษ์สมบูรณ์, ปิติ อ่ำพายัพ та สุรีรัตน์ แซ่ตั้ง. โครงการวิจัยนำร่องอุตสาหกรรมการเลี้ยงกุ้งที่ยั่งยืน : เทคโนโลยีชีวภาพเพื่อการเลี้ยงกุ้งระบบปิดครบวงจร. จุฬาลงกรณ์มหาวิทยาลัย, 2010. https://doi.org/10.58837/chula.res.2010.30.

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โครงการนี้เป็นการวิจัยนำร่องเพื่อการเพาะเลี้ยงกุ้งอย่างยั่งยืน โดยใช้ความรู้ด้านเทคโนโลยีชีวภาพเข้ามาช่วยในการเลี้ยงกุ้งในระบบปิด งานวิจัยนี้มุ่งเน้นศึกษาด้านพันธุศาสตร์และชีววิทยาโมเลกุลของกุ้ง โดยเฉพาะการศึกษายีนในระบบภูมิคุ้มกัน ในสองกลุ่มงานวิจัยหลัก ซึ่งมีหัวข้อวิจัยคือ (1) การวิเคราะห์การทำงานของยีนในระบบโพรฟีนอลออกซิเดสในกุ้ง และ (2) การค้นหายีนที่แสดงออกในการตอบสนองต่อเชื้อโรคโดยวิธี cDNA microarray จากการตรวจสอบหน้าที่ของยีน PmPPAE 2 และ PmLGBP ในระบบโพรฟีนอลออกซิเดสและระบบภูมิคุ้มกันกุ้ง ได้ยับยั้งการแสดงออกของยีนโดยใช้เทคนิค RNA interference พบว่าเมื่อลดการแสดงออกของยีน PmPPAE 2 หรื
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Godwin, Andrew K. Identification of Candidate Breast Cancer Susceptibility Genes Using a cDNA Microarray/CGH Approach. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada408112.

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Godwin, Andrew K. Identification of Candidate Breast Cancer Susceptibility Genes Using a cDNA Microarray/CGH Approach. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada417397.

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Huang, Shixia, and Harold Varmus. The Use of cDNA Microarray to Study Gene Expression in Wnt-1 Induced Mammary Tumors. Defense Technical Information Center, 2002. http://dx.doi.org/10.21236/ada411264.

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Szallasi, Zoltan. CDNA Microarray Based Comparative Gene Expression Analysis of Primary Breast Tumors Versus In Vitro Transformed Neoplastic Breast Epithelium. Defense Technical Information Center, 2001. http://dx.doi.org/10.21236/ada401181.

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Porat, Ron, Gregory T. McCollum, Amnon Lers, and Charles L. Guy. Identification and characterization of genes involved in the acquisition of chilling tolerance in citrus fruit. United States Department of Agriculture, 2007. http://dx.doi.org/10.32747/2007.7587727.bard.

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Citrus, like many other tropical and subtropical fruit are sensitive to chilling temperatures. However, application of a pre-storage temperature conditioning (CD) treatment at 16°C for 7 d or of a hot water brushing (HWB) treatment at 60°C for 20 sec remarkably enhances chilling tolerance and reduces the development of chilling injuries (CI) upon storage at 5°C. In the current research, we proposed to identify and characterize grapefruit genes that are induced by CD, and may contribute to the acquisition of fruit chilling tolerance, by two different molecular approaches: cDNA array analysis an
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Lichter, Amnon, Gopi K. Podila, and Maria R. Davis. Identification of Genetic Determinants that Facilitate Development of B. cinerea at Low Temperature and its Postharvest Pathogenicity. United States Department of Agriculture, 2011. http://dx.doi.org/10.32747/2011.7592641.bard.

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Botrytis cinerea is the postharvest pathogen of many agricultural produce with table grapes, strawberries and tomatoes as major targets. The high efficiency with which B. cinerea causes disease on these produce during storage is attributed in part due to its exceptional ability to develop at very low temperature. Our major goal was to understand the genetic determinants which enable it to develop at low temperature. The specific research objectives were: 1. Identify expression pattern of genes in a coldenriched cDNA library. 2. Identify B. cinerea orthologs of cold-induced genes 3. Profile pro
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