Showing 141 - 160 results of 322 for search '(( elective microarray ) OR ( (selective OR selective) microarray ))', query time: 0.10s Refine Results
  1. 141

    Reprogramming‐derived gene cocktail increases cardiomyocyte proliferation for heart regeneration by Yuan‐Yuan Cheng, Yu‐Ting Yan, David J Lundy, Annie HA Lo, Yu‐Ping Wang, Shu‐Chian Ruan, Po‐Ju Lin, Patrick CH Hsieh

    Published 2016-12-01
    “…Several candidate genes were selected and tested for their ability to induce CM proliferation. …”
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  2. 142

    Comparing gene-gene co-expression network approaches for the analysis of cell differentiation and specification on scRNAseq data by Alisa Pavel, Manja Gersholm Grønberg, Line H. Clemmensen

    Published 2025-01-01
    “…Gene-gene co-expression network analysis has been widely applied to bulk RNA sequencing and microarray data to investigate different phenotypes and compound exposures. …”
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  3. 143
  4. 144

    Multiple colonization with S. pneumoniae before and after introduction of the seven-valent conjugated pneumococcal polysaccharide vaccine. by Silvio D Brugger, Pascal Frey, Suzanne Aebi, Jason Hinds, Kathrin Mühlemann

    Published 2010-07-01
    “…Serotypes were identified by agglutination, multiplex PCR and microarray.<h4>Principal findings</h4>Rate of multiple colonization remained stable up to three years after PCV7 introduction. …”
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  5. 145

    Tissue-restricted expression of Nrf2 and its target genes in zebrafish with gene-specific variations in the induction profiles. by Hitomi Nakajima, Yaeko Nakajima-Takagi, Tadayuki Tsujita, Shin-Ichi Akiyama, Takeshi Wakasa, Katsuki Mukaigasa, Hiroshi Kaneko, Yutaka Tamaru, Masayuki Yamamoto, Makoto Kobayashi

    Published 2011-01-01
    “…Seven zebrafish genes (gstp1, mgst3b, prdx1, frrs1c, fthl, gclc and hmox1a) suitable for WISH analysis were selected from candidates for Nrf2 targets identified by microarray analysis. …”
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  6. 146

    Inferring pathway activity toward precise disease classification. by Eunjung Lee, Han-Yu Chuang, Jong-Won Kim, Trey Ideker, Doheon Lee

    Published 2008-11-01
    “…The advent of microarray technology has made it possible to classify disease states based on gene expression profiles of patients. …”
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  7. 147
  8. 148

    MicroRNA biomarkers of type 2 diabetes: A protocol for corroborating evidence by computational genomics and meta-analyses. by Hongmei Zhu, Siu-Wai Leung

    Published 2021-01-01
    “…Biologically relevant microRNAs will then be selected through genomic database corroboration. Their association with T2D is further measured by area under the curve (AUC) of receive operating characteristic (ROC). …”
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  9. 149

    Exploration of autophagy-related molecular mechanisms underlying epilepsy using multiple datasets by Yongfei Wang, Haoxuan Zeng, Chongxu Liu, Jianjun Chen, Yihong Huang, Xianju Zhou

    Published 2025-08-01
    “…Methods We analyzed GSE143272 and GSE4290 microarray datasets from the NCBI Gene Expression Omnibus database, which is established based on evaluations of peripheral blood samples. …”
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  10. 150

    Integrated Bioinformatics Analysis of Hub Genes and Pathways in Anaplastic Thyroid Carcinomas by Xueren Gao, Jianguo Wang, Shulong Zhang

    Published 2019-01-01
    “…The aim of the present study was to identify hub genes and pathways in ATC by microarray expression profiling. Two independent datasets (GSE27155 and GSE53072) were downloaded from GEO database. …”
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  11. 151

    A Synopsis of Serum Biomarkers in Cutaneous Melanoma Patients by Pierre Vereecken, Frank Cornelis, Nicolas Van Baren, Valérie Vandersleyen, Jean-François Baurain

    Published 2012-01-01
    “…However, the poor sensitivity and specificity of those markers and many other molecules are serious limitations for their routine use in both early (AJCC stage I and II) and advanced stages of melanoma (AJCC stage III and IV). Microarray technology and proteomic research will surely provide new candidates in the near future allowing more accurate definition of the individual prognosis and prediction of the therapeutic outcome and select patients for early adjuvant strategies.…”
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  12. 152

    Maternal bisphenol a exposure impacts the fetal heart transcriptome. by Kalyan C Chapalamadugu, Catherine A Vandevoort, Matthew L Settles, Barrie D Robison, Gordon K Murdoch

    Published 2014-01-01
    “…At the end of treatment, fetal heart tissues were collected and chamber specific transcriptome expression was assessed using genome-wide microarray. Quantitative real-time PCR was conducted on select genes and ventricular tissue glycogen content was quantified. …”
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  13. 153

    Identification and validation of TSPAN13 as a novel temozolomide resistance-related gene prognostic biomarker in glioblastoma. by Haofei Wang, Zhen Liu, Zesheng Peng, Peng Lv, Peng Fu, Xiaobing Jiang

    Published 2025-01-01
    “…Using LASSO Cox analysis, we selected 12 TMZR-RDEGs to construct a risk score model, which was evaluated for performance through survival analysis, time-dependent ROC, and stratified analyses. …”
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  14. 154

    Weighted frequent gene co-expression network mining to identify genes involved in genome stability. by Jie Zhang, Kewei Lu, Yang Xiang, Muhtadi Islam, Shweta Kotian, Zeina Kais, Cindy Lee, Mansi Arora, Hui-Wen Liu, Jeffrey D Parvin, Kun Huang

    Published 2012-01-01
    “…In this study, we used a network mining algorithm to identify tightly connected gene co-expression networks that are frequently present in microarray datasets from 33 types of cancer which were derived from 16 organs/tissues. …”
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  15. 155

    Have maternal or paternal ages any impact on the prenatal incidence of genomic copy number variants associated with fetal structural anomalies? by Marta Larroya, Marta Tortajada, Eduard Mensión, Montse Pauta, Laia Rodriguez-Revenga, Antoni Borrell

    Published 2021-01-01
    “…We conducted a non-paired case-control study (1:2 ratio) among pregnancies undergoing chromosomal microarray analysis (CMA) because of fetal ultrasound anomalies, from December 2012 to May 2020. …”
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  16. 156

    High prevalence of multidrug-tolerant bacteria and associated antimicrobial resistance genes isolated from ornamental fish and their carriage water. by David W Verner-Jeffreys, Timothy J Welch, Tamar Schwarz, Michelle J Pond, Martin J Woodward, Sarah J Haig, Georgina S E Rimmer, Edward Roberts, Victoria Morrison, Craig Baker-Austin

    Published 2009-12-01
    “…<h4>Methodology/principal findings</h4>To assess the potential effects of this sustained selection pressure, 127 Aeromonas spp. isolated from warm and cold water ornamental fish species were screened for tolerance to 34 antimicrobials. …”
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  17. 157

    Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics Methods by Mufang Feng, Jie Ji, Xiaoliu Li, Xinming Ye

    Published 2022-01-01
    “…To determine the effects of exercise and time on human skeletal muscle, we downloaded the microarray expression profile of GSE1832 and analyzed it to select differentially expressed genes (DEGs). …”
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  18. 158

    Apoptosis-associated genetic mechanisms in the transition from rheumatoid arthritis to osteoporosis: A bioinformatics and functional analysis approach by Hao-Ju Lo, Chun-Hao Tsai, Tsan-Wen Huang

    Published 2024-12-01
    “…This study explores the mechanisms of glucocorticoid-induced osteoporosis (OP) and Rheumatoid arthritis (RA), focusing on apoptosis and its role in the progression from RA to OP. Using microarray data from the GEO database, differential gene expression analysis was conducted with the limma package, identifying significant genes in RA and OP. …”
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  19. 159

    Cuproptosis genes in predicting the occurrence of allergic rhinitis and pharmacological treatment. by Ting Yi

    Published 2025-01-01
    “…<h4>Results</h4>Four AR signature genes (MRPS30, CLPX, MRPL13, and MRPL53) were selected by the MCC, EPC, BottleNeck, and Closeness algorithms. …”
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  20. 160

    SMART: unique splitting-while-merging framework for gene clustering. by Rui Fa, David J Roberts, Asoke K Nandi

    Published 2014-01-01
    “…Moreover, two real microarray gene expression datasets are studied using this approach. …”
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