Showing 61 - 80 results of 1,096 for search '(( effective microarray ) OR ((( selection microarray ) OR ( detection microarray ))))', query time: 0.14s Refine Results
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    Global effects of DNA replication and DNA replication origin activity on eukaryotic gene expression by Larsson Omberg, Joel R Meyerson, Kayta Kobayashi, Lucy S Drury, John F X Diffley, Orly Alter

    Published 2009-10-01
    “…This confirms previous predictions from mathematical modeling of a global causal coordination between DNA replication origin activity and mRNA expression, and shows that mathematical modeling of DNA microarray data can be used to correctly predict previously unknown biological modes of regulation.…”
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    Article
  3. 63

    Using effective subnetworks to predict selected properties of gene networks. by Gemunu H Gunaratne, Preethi H Gunaratne, Lars Seemann, Andrei Török

    Published 2010-10-01
    “…Steady state measurements of these influence networks can be obtained from DNA microarray experiments. However, since they contain a large number of nodes, the computation of influence networks requires a prohibitively large set of microarray experiments. …”
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    Identification of potential biomarkers and pathways related to major depressive disorder by integrated bioinformatic analysis and experimental validation by Ying Zeng, Lu-Qi Peng, Mei Zhang, Rong Zhong, Ke-Chao Nie, Wei Huang

    Published 2025-05-01
    “…Objective: To identify promising biomarkers for the pathogenesis of major depressive disorder (MDD). Methods: Microarray chips of MDD patients, including the GSE98793, GSE52790, and GSE39653 datasets, were obtained from the Gene Expression Omnibus database. …”
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  6. 66

    Expression of long non-coding RNA in patients with non-IgA mesangial proliferative glomerulonephritis by CONG Shan, SUI Wei-guo, ZOU Gui-mian, XUE Wen, LI Huan, YAN Qiang, CHEN Jie-jing, LUO Ya-dan, CHEN Huai-zhou

    Published 2015-01-01
    “…Objective To study differential expression profile of mRNA and long non-coding RNA(IncRNA) through microarray analysis between non-IgA mesangial proliferative glomerulonephritis(MsPGN) patients and the controls,and then explore the potential role of IncRNA in the pathogenesis of non-IgA MsPGN.Methods Through simple random sampling,4 patients with non-IgA MsPGN and 2 controls were selected as disease group and control group,respectively.Renal cortical tissues from two groups were collected.Total RNA was extracted,quantified and prepared to ds-cDNA through reverse transcription ds-cDNA was labeled with NimbleGen one-color DNA labeling kit and used for array hybridization.All experimental data were processed through GO analysis,Pathway analysis and the gene loci correlation analysis of mRNA and IncRNA.Some IncRNAs that were closely related to non-IgA MsPGN were screened out.Finally,part of the array results was detected by PCR to verify the reliability of array test Results By fold change filtering,4317 differentially expressed mRNAs and 3502 differentially expressed IncRNAs were screened out.Five IncRNAs were found to play potential roles in the pathogenesis of non-IgA MsPGN:AF1180924(close to coding gene FGG),AK092233(close to coding gene COL18A1),AK130579(close to coding gene CREBBP),AK023598(close to coding gene LEPR),and AK055915(close to coding gene CDC42EP3).These results provided an important basis for revealing the pathogenesis of non-IgA MsPGN.Conclusions Some IncRNAs can potentially regulate related genes and plays an important role in the pathogenesis and development of non-IgA MsPGN.…”
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    Optimized T7 Amplification System for Microarray Analysis by C. Pabón, Z. Modrusan, M.V. Ruvolo, I.M. Coleman, S. Daniel, H. Yue, L.J. Arnold, M.A. Reynolds

    Published 2001-10-01
    “…Glass cDNA microarray technologies offer a highly parallel approach for profiling expressed gene sequences in disease-relevant tissues. …”
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  9. 69

    A two stage grading approach for feature selection and classification of microarray data using Pareto based feature ranking techniques: A case study by Rasmita Dash

    Published 2020-02-01
    “…High dimensional search space in microarray data with large number of genes and few dozen of samples increases the complexity of analysis of such databases. …”
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  10. 70

    Microarray analysis of the effects of Acthar Gel versus methylprednisolone in a model of focal segmental glomerulosclerosis in female rats by Kyle Hayes, Dale Wright

    Published 2025-04-01
    “…On Day 56, animals were sacrificed, and RNA samples of kidney cortex tissue were analyzed using microarrays. Compared with control, Acthar significantly decreased the expression of more genes related to inflammation, immune function, and fibrosis than MP. …”
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  11. 71

    Genetic etiology and pregnancy outcomes of fetal hyperechoic kidneys: a retrospective analysis by Meiying Cai, Na Lin, Ziheng Xiao, Ziheng Xiao, Hailong Huang, Lin Zheng, Liangpu Xu

    Published 2025-08-01
    “…Chromosome karyotyping and chromosomal microarray analysis (CMA) were performed on fetuses displaying this phenotype on prenatal ultrasound. …”
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  12. 72

    Analysis of a Series of 26 Cases With Prenatal Skeletal Dysplasia via Multiplatform Genetic Detection by Li‐min Cui, Hua‐ying Hu, Xiao‐mei Zhai, Ming‐fei Qi, Yan‐ming Liu, Cong‐ying Han, Jing Zhang, Ming Shen, Yu‐lan Xiang, Wen‐qi Chen, Kai Yang, Dong‐liang Zhang, Huan‐xia Xing

    Published 2025-01-01
    “…Materials and Methods In this study, we recruited 26 cases of SD and analyzed them with a designed sequential genetic detection. Chromosome karyotyping, microarray analysis (CMA), and whole exome sequencing (WES) techniques are performed as needed. …”
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    Listen to genes: dealing with microarray data in the frequency domain. by Jianfeng Feng, Dongyun Yi, Ritesh Krishna, Shuixia Guo, Vicky Buchanan-Wollaston

    Published 2009-01-01
    “…<h4>Background</h4>We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes.…”
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    Application of chromosome microarray analysis and karyotyping in fetal cardiac abnormalities by Yun Guo, Xiaoqin Xin, Linju Zhou, Jungao Huang

    Published 2025-06-01
    “…Chromosome microarray analysis detected abnormalities in 6.58% (5/76) of the isolated cardiac abnormalities group and 27.27% (6/22) in the group with combined abnormalities, showing a significant statistical difference (P &lt; 0.05). …”
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    Transfer learning for accelerated failure time model with microarray data by Yan-Bo Pei, Zheng-Yang Yu, Jun-Shan Shen

    Published 2025-03-01
    “…Abstract Background In microarray prognostic studies, researchers aim to identify genes associated with disease progression. …”
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