Academic literature on the topic 'Gene Array'
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Journal articles on the topic "Gene Array"
Zhang, Xiaoling, Marc E. Lenburg, and Avrum Spira. "Comparison of Nasal Epithelial Smoking-Induced Gene Expression on Affymetrix Exon 1.0 and Gene 1.0 ST Arrays." Scientific World Journal 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/951416.
Full textAschheim, Kathy. "Gene detection by array." Nature Biotechnology 18, no. 11 (November 2000): 1129. http://dx.doi.org/10.1038/81066.
Full textThomas, E. V., K. H. Phillippy, B. Brahamsha, D. M. Haaland, J. A. Timlin, L. D. H. Elbourne, B. Palenik, and I. T. Paulsen. "Statistical Analysis of Microarray Data with Replicated Spots: A Case Study withSynechococcusWH8102." Comparative and Functional Genomics 2009 (2009): 1–11. http://dx.doi.org/10.1155/2009/950171.
Full textGellert, Pascal, Mizue Teranishi, Katharina Jenniches, Piera De Gaspari, David John, Karsten grosse Kreymborg, Thomas Braun, and Shizuka Uchida. "Gene Array Analyzer: alternative usage of gene arrays to study alternative splicing events." Nucleic Acids Research 40, no. 6 (November 28, 2011): 2414–25. http://dx.doi.org/10.1093/nar/gkr1110.
Full textWalsh, James Bruce. "Persistence of Tandem Arrays: Implications for Satellite and Simple-Sequence DNAs." Genetics 115, no. 3 (March 1, 1987): 553–67. http://dx.doi.org/10.1093/genetics/115.3.553.
Full textAlkahtani, Mohammed, Yihua Hu, Zuyu Wu, Colin Sokol Kuka, Muflih S. Alhammad, and Chen Zhang. "Gene Evaluation Algorithm for Reconfiguration of Medium and Large Size Photovoltaic Arrays Exhibiting Non-Uniform Aging." Energies 13, no. 8 (April 14, 2020): 1921. http://dx.doi.org/10.3390/en13081921.
Full textMocellin, Simone, Maurizio Provenzano, Carlo Riccardo Rossi, Pierluigi Pilati, Donato Nitti, and Mario Lise. "DNA Array-Based Gene Profiling." Annals of Surgery 241, no. 1 (January 2005): 16–26. http://dx.doi.org/10.1097/01.sla.0000150157.83537.53.
Full textO'Neill, Paul. "Gene array breakthrough for glioblastoma." Trends in Molecular Medicine 7, no. 9 (September 2001): 387. http://dx.doi.org/10.1016/s1471-4914(01)02145-1.
Full textAOKI, Hiroshi, Akiko KITAJIMA, and Hiroaki TAO. "Electrochemical Gene Sensor Arrays Prepared Using Non-contact Nanoliter Array Spotting of Gene Probes." Analytical Sciences 26, no. 3 (2010): 367–70. http://dx.doi.org/10.2116/analsci.26.367.
Full textJohnston, Mark. "Gene chips: Array of hope for understanding gene regulation." Current Biology 8, no. 5 (February 1998): R171—R174. http://dx.doi.org/10.1016/s0960-9822(98)70103-4.
Full textDissertations / Theses on the topic "Gene Array"
Li, Yan 1978 July 15. "Gene expression array simulator." Thesis, Massachusetts Institute of Technology, 2002. http://hdl.handle.net/1721.1/87263.
Full text"May 10, 2002.
Includes bibliographical references (leaf 141).
by Yan Li.
M.Eng.
Mapiye, Darlington S. "Normalization and statistical methods for crossplatform expression array analysis." University of the Western Cape, 2012. http://hdl.handle.net/11394/4586.
Full textA large volume of gene expression data exists in public repositories like the NCBI’s Gene Expression Omnibus (GEO) and the EBI’s ArrayExpress and a significant opportunity to re-use data in various combinations for novel in-silico analyses that would otherwise be too costly to perform or for which the equivalent sample numbers would be difficult to collects exists. For example, combining and re-analysing large numbers of data sets from the same cancer type would increase statistical power, while the effects of individual study-specific variability is weakened, which would result in more reliable gene expression signatures. Similarly, as the number of normal control samples associated with various cancer datasets are often limiting, datasets can be combined to establish a reliable baseline for accurate differential expression analysis. However, combining different microarray studies is hampered by the fact that different studies use different analysis techniques, microarray platforms and experimental protocols. We have developed and optimised a method which transforms gene expression measurements from continuous to discrete data points by grouping similarly expressed genes into quantiles on a per-sample basis. After cross mapping each probe on each chip to the gene it represents, thereby enabling us to integrate experiments based on genes they have in common across different platforms. We optimised the quantile discretization method on previously published prostate cancer datasets produced on two different array technologies and then applied it to a larger breast cancer dataset of 411 samples from 8 microarray platforms. Statistical analysis of the breast cancer datasets identified 1371 differentially expressed genes. Cluster, gene set enrichment and pathway analysis identified functional groups that were previously described in breast cancer and we also identified a novel module of genes encoding ribosomal proteins that have not been previously reported, but whose overall functions have been implicated in cancer development and progression. The former indicates that our integration method does not destroy the statistical signal in the original data, while the latter is strong evidence that the increased sample size increases the chances of finding novel gene expression signatures. Such signatures are also robust to inter-population variation, and show promise for translational applications like tumour grading, disease subtype classification, informing treatment selection and molecular prognostics.
Lundén, Karl. "Heterobasidion - conifer pathosystem : heterologous array analysis and transcriptional shift from saprotrophic to necrotrophic growth /." Uppsala : Department of Forest Mycology and Pathology, Swedish University of Agricultural Sciences, 2010. http://epsilon.slu.se/201019.pdf.
Full textNorouzi, Masoud. "Development of an RNA array to Protein array (RAPA) platform and its application to gene expression analysis of synthetic riboregulators." Thesis, University of Portsmouth, 2018. https://researchportal.port.ac.uk/portal/en/theses/development-of-an-rna-array-to-protein-array-rapa-platform-and-its-application-to-gene-expression-analysis-of-synthetic-riboregulators(5867a39c-55a4-410a-8e5a-53c347b8a81a).html.
Full textBjork, Kathe Elizabeth. "Robust identification of differential gene expression and discrimination /." Connect to full text via ProQuest. Limited to UCD Anschutz Medical Campus, 2006.
Find full textTypescript. Includes bibliographical references (leaves 237-239). Free to UCDHSC affiliates. Online version available via ProQuest Digital Dissertations;
Araujo, Tânia Kawasaki de 1985. "Utilização da técnica de Open Array para investigação de genes associados a fendas labiopalatais em amostra da população brasileira." [s.n.], 2015. http://repositorio.unicamp.br/jspui/handle/REPOSIP/313118.
Full textTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Ciências Médicas
Made available in DSpace on 2018-08-27T00:02:24Z (GMT). No. of bitstreams: 1 Araujo_TaniaKawasakide_D.pdf: 3447671 bytes, checksum: 97911848c6334882843e4b270b9c6771 (MD5) Previous issue date: 2015
Resumo: A fenda de labiopalatal (FLP) isolada é o defeito craniofacial mais comum em humanos. O objetivo deste estudo foi avaliar associações entre 39 genes e a etiologia de FLP isolada em uma amostra da população brasileira. Este estudo de associação do tipo caso-controle foi desenhado com um poder estatístico de 81,29% por meio de regressão logística. O grupo de casos foi composto por 182 pacientes com FLP isolada registrados na Base Brasileira de Dados Clínicos e Familiais de Fendas Orofaciais Típicas. O grupo controle foi formado por 355 indivíduos saudáveis, sem história de fendas orais em três gerações. Toda a amostra foi genotipada por meio do sistema OpenArray®TaqManTM para 253 polimorfismos de nucleotídeo único (SNPs) em 39 genes, incluindo dois genes que, recentemente, haviam sido descritos por este grupo de pesquisa. A seleção de SNPs foi feita com o programa SNPbrowser 4.0 (Applied Biosystems) para verificar o número e a localização dos SNPs apropriados para explorar a associação de cada gene com FLP isolada. A análise de associação foi realizada por meio de regressão logística e regressão stepwise. Os resultados foram corrigidos para múltiplos testes (correção de Bonferroni). Vinte e quatro SNPs em 16 genes foram significativamente associados com a etiologia da FLP isolada, incluindo MSX1, SPRY1, MSX2, PRSS35, TFAP2A, SHH, VAX1, TBX10, WNT11, PAX9, BMP4, JAG2, AXIN2, DVL2, KIF7 e TCBE3. A análise de regressão stepwise revelou que 11 genes contribuiram em 15,5% do fenótipo de FLP isolada nessa amostra. Este é o primeiro estudo a associar os genes KIF7 e TCEB3 à FLP isolada
Abstract: Nonsyndromic cleft lip and palate (NSCLP) is the most common craniofacial birth defect. The aim of this study was to evaluate associations between 39 genes and the etiology of NSCLP in a Brazilian population. This case-control association study was designed with 81.29% statistical power according to logistic regression. The case group was composed of 182 patients with NSCLP enrolled in the Brazilian Database on Orofacial Clefts. The controls included 355 healthy individuals with no history of oral clefting in the past three generations. All samples were genotyped by TaqMan®OpenArrayTM system for 253 single nucleotide polymorphisms (SNPs) in 39 genes, including two that had recently been associated with this process. The SNPs selection was made by SNPbrowser 4.0 (Applied Biosystems) in order to establish the best SNPs to explor the association between each gene and NSCLP. The association analysis was performed using logistic regression and stepwise regression. The results were corrected for multiple testing (Bonferroni correction). Twenty-four SNPs in 16 genes were significantly associated with the etiology of NSCLP, including MSX1, SPRY1, MSX2, PRSS35, TFAP2A, SHH, VAX1, TBX10, WNT11, PAX9, BMP4, JAG2, AXIN2, DVL2, KIF7 and TCBE3. Stepwise regression analysis revealed that 11 genes contributed to 15.5% of the phenotype of NSCLP in the sample. This is the first study to associate KIF7 and TCEB3 with NSCLP
Doutorado
Ciencias Biomedicas
Doutora em Ciências Médicas
Arlinde, Christina. "Gene expression profiling in animal models of alcoholism /." Stockholm, 2004. http://diss.kib.ki.se/2004/91-7140-133-4/.
Full textSandgren, Johanna. "Array-based Genomic and Epigenomic Studies in Healthy Individuals and Endocrine Tumours." Doctoral thesis, Uppsala universitet, Institutionen för kirurgiska vetenskaper, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-129533.
Full textDumas, Laura Jane. "Gene copy number variation in human and primate evolution /." Connect to full text via ProQuest. Limited to UCD Anschutz Medical Campus, 2008. http://proquest.umi.com/pqdweb?did=1545571861&sid=1&Fmt=6&clientId=18952&RQT=309&VName=PQD.
Full textTypescript. Includes bibliographical references (leaves 98-112). Free to UCD Anschutz Medical Campus. Online version available via ProQuest Digital Dissertations;
Tong, Lily. "Probing the function of RNase E family using biochemical techniques and gene array technology." Thesis, University of Leeds, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.414514.
Full textBooks on the topic "Gene Array"
Muller, Hans-Joachim. Microarrays. Burlington, MA: Elsevier Academic Press, 2005.
Find full textGene network inference: Verification of methods for systems genetics data. Heidelberg: Springer, 2013.
Find full text1966-, Scherer Andreas, ed. Batch effects and noise in microarray experiments, sources, and solutions. Chichester, West Sussex: J. Wiley, 2009.
Find full textThomas, Roeder, ed. Microarrays. Burlington, MA: Elsevier Academic Press, 2006.
Find full textT, Kho Alvin, and Butte Atul J, eds. Microarrays for an integrative genomics. Cambridge, Mass: MIT Press, 2003.
Find full text1965-, Blalock Eric M., ed. A beginner's guide to microarrays. Boston: Kluwer Academic Publishers, 2003.
Find full textFormalin-fixed paraffin-embedded tissues: Methods and protocols. New York: Humana Press, 2011.
Find full text1961-, Ye S., and Day Ian N. M, eds. Microarrays & microplates: Applications in biomedical sciences. Oxford: BIOS, 2003.
Find full textMicroarray analysis. Hoboken, NJ: Wiley-Liss, 2003.
Find full textBeadchip molecular immunohematology: Toward routine donor and patient antigen profiling by DNA analysis. New York: Springer, 2011.
Find full textBook chapters on the topic "Gene Array"
Lam, Ching-Wan, and Kin-Chong Lau. "Candidate Screening through High-Density SNP Array." In Gene Discovery for Disease Models, 195–214. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9780470933947.ch10.
Full textDorris, David, Chang-gong Liu, Ramesh Ramakrishnan, Richard Shippy, Sangeet Singh-Gasson, Anna Lublinsky, Edward Touma, et al. "Oligonucleotide Array Technologies for Gene Expression Profiling." In Biochips, 1–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05092-7_1.
Full textJovanovic, Borko D., Raymond C. Bergan, and Warren A. Kibbe. "Some Aspects of Analysis of Gene Array Data." In Biostatistical Applications in Cancer Research, 71–89. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3571-0_5.
Full textDickson, Glenda J., Terence R. Lappin, and Alexander Thompson. "Complete Array of HOX Gene Expression by RQ-PCR." In Leukemia, 369–93. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-59745-418-6_19.
Full textLidén, Per, Lars Asker, and Henrik Bostróm. "Rule Induction for Classification of Gene Expression Array Data." In Principles of Data Mining and Knowledge Discovery, 338–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45681-3_28.
Full textGonzález Calabozo, José María, Carmen Peláez-Moreno, and Francisco José Valverde-Albacete. "Gene Expression Array Exploration Using $\mathcal{K}$ -Formal Concept Analysis." In Formal Concept Analysis, 119–34. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20514-9_11.
Full textArcher, T. K., M. G. Cordingley, V. Marsaud, H. Richard-Foy, and G. L. Hager. "Steroid Transactivation at a Promoter Organized in a Specifically-Positioned Array of Nucleosomes." In The Steroid/Thyroid Hormone Receptor Family and Gene Regulation, 221–38. Basel: Birkhäuser Basel, 1989. http://dx.doi.org/10.1007/978-3-0348-5466-5_16.
Full textAigner, Thomas, Pia M. Gebhard, and Alexander Zien. "Gene expression profiling by the cDNA array technology: Molecular portraying of chondrocytes." In The Many Faces of Osteoarthritis, 293–96. Basel: Birkhäuser Basel, 2002. http://dx.doi.org/10.1007/978-3-0348-8133-3_29.
Full textWong, Kwong-Kwok. "Use of Single-Nucleotide Polymorphism Array for Tumor Aberrations in Gene Copy Numbers." In Genomics and Pharmacogenomics in Anticancer Drug Development and Clinical Response, 75–88. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-60327-088-5_6.
Full textJovanovic, Borko D., Shuguang Huang, Yuequin Liu, Karen N. Naguib, and Raymond C. Bergan. "An Analysis of Gene Array Data Related to Cell Adhesion and Prostate Cancer." In Biostatistical Applications in Cancer Research, 91–111. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4757-3571-0_6.
Full textConference papers on the topic "Gene Array"
Neitz, Maureen. "Molecular genetics of red-green color vision." In OSA Annual Meeting. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oam.1990.fm2.
Full textCaffarena, G., S. Bojanic, J. A. Lopez, C. Pedreira, and O. Nieto-Taladriz. "High-speed systolic array for gene matching." In Proceeding of the 2004 ACM/SIGDA 12th international symposium. New York, New York, USA: ACM Press, 2004. http://dx.doi.org/10.1145/968280.968325.
Full textPaik, S. J., S. Park, V. Zarnitsyn, M. R. Prausnitz, M. G. Allen, S. Choi, and X. D. Guo. "A HIGHLY DENSE NANONEEDLE ARRAY FOR INTRACELLULAR GENE DELIVERY." In 2012 Solid-State, Actuators, and Microsystems Workshop. San Diego: Transducer Research Foundation, 2012. http://dx.doi.org/10.31438/trf.hh2012.40.
Full textVenkatesh, E. T., P. Tangaraj, and S. Chitra. "Classification of cancer gene expressions from micro-array analysis." In 2010 International Conference on Innovative Computing Technologies (ICICT). IEEE, 2010. http://dx.doi.org/10.1109/icinnovct.2010.5440095.
Full textHu, Jing, Jianbo Gao, Yinhe Cao, and Weijia Zhang. "Detection of gene copy number change in array CGH data." In 2006 IEEE/NLM Life Science Systems and Applications Workshop. IEEE, 2006. http://dx.doi.org/10.1109/lssa.2006.250402.
Full textRehna, V. J., and G. Raju. "Signal extraction from microarray images for gene array data analysis." In 2nd International Conference on Computer and Automation Engineering (ICCAE 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccae.2010.5451859.
Full textDror, Ron O., Jonathan G. Murnick, Nicola A. Rinaldi, Voichita D. Marinescu, Ryan M. Rifkin, and Richard A. Young. "A bayesian approach to transcript estimation from gene array data." In the sixth annual international conference. New York, New York, USA: ACM Press, 2002. http://dx.doi.org/10.1145/565196.565213.
Full textTian, David, and Keith Burley. "Classification of micro-array gene expression data using neural networks." In 2010 International Joint Conference on Neural Networks (IJCNN). IEEE, 2010. http://dx.doi.org/10.1109/ijcnn.2010.5596568.
Full textRamalingam, Naveen, Long-Qing Chen, Xin-Hao Yang, Liqun Deng, Qing-Hui Wang, Eric Yap Peng Huat, Chiew Hoon Neo, and Hai-Qing Gong. "A Surface-Directed Microfluidic Scheme for Parallel Nanoliter PCR Array Suitable for Point-of-Care Testing." In ASME 2009 7th International Conference on Nanochannels, Microchannels, and Minichannels. ASMEDC, 2009. http://dx.doi.org/10.1115/icnmm2009-82052.
Full textChretien, Stephane, Christophe Guyeux, Michael Boyer-Guittaut, Regis Delage-Mouroux, and Francoise Descotes. "Investigating gene expression array with outliers and missing data in bladder cancer." In 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2015. http://dx.doi.org/10.1109/bibm.2015.7359819.
Full textReports on the topic "Gene Array"
Fluhr, Robert, and Volker Brendel. Harnessing the genetic diversity engendered by alternative gene splicing. United States Department of Agriculture, December 2005. http://dx.doi.org/10.32747/2005.7696517.bard.
Full textTu, Q., Ye Deng, Lu Lin, Chris L. Hemme, Zhili He, and Jizhong Zhou. HuMiChip: Development of a Functional Gene Array for the Study of Human Microbiomes. Office of Scientific and Technical Information (OSTI), May 2010. http://dx.doi.org/10.2172/1008326.
Full textXu, Jin-Rong, and Amir Sharon. Comparative studies of fungal pathogeneses in two hemibiotrophs: Magnaporthe grisea and Colletotrichum gloeosporioides. United States Department of Agriculture, May 2008. http://dx.doi.org/10.32747/2008.7695585.bard.
Full textSteffens, John, Eithan Harel, and Alfred Mayer. Coding, Expression, Targeting, Import and Processing of Distinct Polyphenoloxidases in Tissues of Higher Plants. United States Department of Agriculture, November 1994. http://dx.doi.org/10.32747/1994.7613008.bard.
Full textLevin, Ilan, Avtar K. Handa, Avraham Lalazar, and Autar K. Mattoo. Modulating phytonutrient content in tomatoes combining engineered polyamine metabolism with photomorphogenic mutants. United States Department of Agriculture, December 2006. http://dx.doi.org/10.32747/2006.7587724.bard.
Full textSeroussi, Eyal, and George Liu. Genome-Wide Association Study of Copy Number Variation and QTL for Economic Traits in Holstein Cattle. United States Department of Agriculture, September 2010. http://dx.doi.org/10.32747/2010.7593397.bard.
Full textAbbo, Shahal, Hongbin Zhang, Clarice Coyne, Amir Sherman, Dan Shtienberg, and George J. Vandemark. Winter chickpea; towards a new winter pulse for the semiarid Pacific Northwest and wider adaptation in the Mediterranean basin. United States Department of Agriculture, January 2011. http://dx.doi.org/10.32747/2011.7597909.bard.
Full textBercovier, Herve, and Ronald P. Hedrick. Diagnostic, eco-epidemiology and control of KHV, a new viral pathogen of koi and common carp. United States Department of Agriculture, December 2007. http://dx.doi.org/10.32747/2007.7695593.bard.
Full textPorat, 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, December 2007. http://dx.doi.org/10.32747/2007.7587727.bard.
Full textHorwitz, Benjamin, and Barbara Gillian Turgeon. Secondary Metabolites, Stress, and Signaling: Roles and Regulation of Peptides Produced by Non-ribosomal Peptide Synthetases. United States Department of Agriculture, 2005. http://dx.doi.org/10.32747/2005.7696522.bard.
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