Showing 41 - 60 results of 457 for search 'detection microarray', query time: 0.06s Refine Results
  1. 41

    Chromosomal Microarray in Children Born Small for Gestational Age – Single Center Experience by Perović D, Barzegar P, Damnjanović T, Jekić B, Grk M, Dušanović Pjević M, Cvetković D, Đuranović Uklein A, Stojanovski N, Rašić M, Novaković I, Elhayani B, Maksimović N

    Published 2025-03-01
    “…Notably, advancements in cytogenetic techniques have shifted from routine karyotyping to the recommended use of microarray technology. This transition allows higher resolution and the detection of sub-microscopic copy number variants (CNVs).…”
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  2. 42

    Chromosomal Microarray Analysis in Spina Bifida: Genetic Heterogeneity and Its Clinical Implications by Himani Pandey, Jyoti Sharma, Sourabh Kumar, Nakul Mohan, Vishesh Jain, Anjan Kumar Dhua, Devendra Kumar Yadav, Ashish Kumar Dubey, Prativa Choudhury, Prabudh Goel

    Published 2025-05-01
    “…While whole exome sequencing has identified several pathogenic variants in Indian cohorts, the role of chromosomal imbalances and long contiguous stretches of homozygosity (LCSHs) remains largely unexplored in this population. Chromosomal microarray analysis (CMA) is an important tool that provides insights into such genetic aberrations, making it significant for evaluating patients with spina bifida. …”
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  3. 43

    Chromosomal microarray on product of conception in early pregnancy loss: A case report by Snehal Mallakmir, Gauri Mulgund, Rashid Merchant

    Published 2023-01-01
    “…Evaluation of products of conception (POC) is very important to detect chromosomal abnormalities associated with RPL. …”
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  4. 44

    Reuse of cDNA microarrays hybridized with cRNA by stripping with RNase H by Haoxiang Wu, James A Bynum, Salomon Stavchansky, Phillip D. Bowman

    Published 2008-11-01
    “…Additionally, statistical class comparison analysis globally indicated that there were essentially no differences detected following three hybridizations. Dye-swapped microarrays produced similar results. …”
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  5. 45

    Identification of gastric cancer biomarkers through in-silico analysis of microarray based datasets by Arbaz Akhtar, Yasir Hameed, Samina Ejaz, Iqra Abdullah

    Published 2024-12-01
    “…For this purpose, the ten microarray-based gene expression datasets (GSE54129, GSE79973, GSE161533, GSE103236, GSE33651, GSE19826, GSE118916, GSE112369, GSE13911, and GSE81948) were retrieved from GEO database and analyzed by GEO2R to identify differentially expressed genes. …”
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  6. 46

    A comprehensive microarray-based DNA methylation study of 367 hematological neoplasms. by Jose I Martin-Subero, Ole Ammerpohl, Marina Bibikova, Eliza Wickham-Garcia, Xabier Agirre, Sara Alvarez, Monika Brüggemann, Stefanie Bug, Maria J Calasanz, Martina Deckert, Martin Dreyling, Ming Q Du, Jan Dürig, Martin J S Dyer, Jian-Bing Fan, Stefan Gesk, Martin-Leo Hansmann, Lana Harder, Sylvia Hartmann, Wolfram Klapper, Ralf Küppers, Manuel Montesinos-Rongen, Inga Nagel, Christiane Pott, Julia Richter, José Román-Gómez, Marc Seifert, Harald Stein, Javier Suela, Lorenz Trümper, Inga Vater, Felipe Prosper, Claudia Haferlach, Juan Cruz Cigudosa, Reiner Siebert

    Published 2009-09-01
    “…<h4>Methodology/principal findings</h4>Here, we report for the first time a microarray-based DNA methylation study of 767 genes in 367 HNs diagnosed with 16 of the most representative B-cell (n = 203), T-cell (n = 30), and myeloid (n = 134) neoplasias, as well as 37 samples from different cell types of the hematopoietic system. …”
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  7. 47

    A Network Analysis Approach to Detect and Differentiate Usher Syndrome Types Using miRNA Expression Profiles: A Pilot Study by Rama Krishna Thelagathoti, Wesley A. Tom, Chao Jiang, Dinesh S. Chandel, Gary Krzyzanowski, Appolinaire Olou, Rohan M. Fernando

    Published 2024-11-01
    “…<b>Methods:</b> We collected microarray miRNA-expression data from 17 samples, representing four patient-derived USH cell lines and a non-USH control. …”
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  8. 48
  9. 49

    Etiological diagnosis of miscarriage by combining use of chromosomal microarray analysis and whole-exome sequencing by Jianlong Zhuang, Wanyu Fu, Ling Gu, Xiaofang Ye, Junyu Wang, Chunnuan Chen

    Published 2025-07-01
    “…Abstract Background Chromosomal microarray analysis (CMA) is being increasingly used to reveal the genetic causes of miscarriage. …”
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  10. 50

    The assessing of clinical relevance of chromosomal microarray analysis in the prenatal diagnosis of fetal growth restriction by Peng Li, Wenli Wu, Xiaoyun Zhang, Yuting Li, Miao Liu, Yanping Wang, Dongmei Man, Fengge Wang

    Published 2025-02-01
    “…Here, we intend to investigate the significance of Chromosomal Microarray Analysis (CMA) in the prenatal diagnosis of definite FGR. …”
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  11. 51

    Microarray technologies for analysis of genetic determinants of <i>Neisseria gonorrhoeae</i> antimicrobial resistance by Boris L. Shaskolskiy, Dmitry V. Kravtsov, Ilya D. Kandinov, Dmitry A. Gryadunov, Marina V. Shpilevaya, Julia Z. Shagabieva, Nikita Y. Nosov

    Published 2025-03-01
    “…Conclusion. Microarray technologies for detecting antimicrobial resistance genetic determinants in N. gonorrhoeae serve as a complementary tool for identifying resistant strains. …”
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  12. 52

    Genetic Evaluation of Early Pregnancy Loss by Chromosomal Microarray Analysis: A Retrospective Analysis by Hu Ding, Honglei Duan, Xiangyu Zhu, Wei Liu, Leilei Gu, Chunxiang Zhou, Jie Li

    Published 2025-07-01
    “…This retrospective cohort study utilizes chromosomal microarray analysis (CMA) to systematically investigate chromosomal abnormalities associated with early pregnancy loss. …”
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  13. 53
  14. 54

    The use of chromosomal microarray analysis for diagnostics of chromosomal pathology in fetal central nervous system malformations by J. K. Kievskaya, I. V. Kanivets, E. V. Kudryavtseva, D. V. Pyankov, S. A. Korostelev

    Published 2020-10-01
    “…There were enrolled 42 pregnant women underwent invasive prenatal diagnostics in 2013–2019 due to ultrasound detection of congenital CNS defect in fetus. Fetal samples were studied by using chromosome microarray analysis (CMA).Results. …”
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  15. 55

    Circular RNA microarray expression profile and potential function of circDOCK1 in colorectal cancer by Guojing Zhang, Xiaoyan Wu, Hongmin Fu, Daqing Sun

    Published 2025-02-01
    “…Therefore, there exists a critical need to identify novel markers facilitating early CRC detection and prognosis. Circular RNAs (circRNAs) hold promise as novel clinical diagnostic markers. …”
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  16. 56

    SNP Microarray in FISH Negative Clinically Suspected 22q11.2 Microdeletion Syndrome by Ashutosh Halder, Manish Jain, Amanpreet Kaur Kalsi

    Published 2016-01-01
    “…Clinically suspected specific deletions (22q11.2) were detectable in approximately 8% of cases by SNP microarray, mostly from FISH noninformative cases. …”
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  17. 57

    Microarray analysis of virulence gene profiles in Salmonella serovars from food/food animal environment by Wen Zou, Sufian F Al-Khaldi, William S Branham, Tao Han, James C Fuscoe, Jing Han, Steven L Foley, Joshua Xu, Hong Fang, Carl E Cerniglia, Rajesh Nayak

    Published 2010-09-01
    “…In general, genes belonging to inv, pip, prg, sic, sip, spa or ttr families were detected in more than 90% of the isolates, while the iacP, avrA, invH, rhuM, sirA, sopB, sopE or sugR genes were detected in 40 to 80% of the isolates.  …”
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  18. 58

    Distinct antibody responses of patients with mild and severe leptospirosis determined by whole proteome microarray analysis. by Carolina Lessa-Aquino, Janet C Lindow, Arlo Randall, Elsio Wunder, Jozelyn Pablo, Rie Nakajima, Algis Jasinskas, Jaqueline S Cruz, Alcineia O Damião, Nívison Nery, Guilherme S Ribeiro, Federico Costa, José E Hagan, Mitermayer Galvão Reis, Albert I Ko, Marco Alberto Medeiros, Philip L Felgner

    Published 2017-01-01
    “…<h4>Methods and principal findings</h4>Here, we used protein microarray chip to profile the antibody responses of patients with severe and mild leptospirosis against the complete Leptospira interrogans serovar Copenhageni predicted ORFeome. …”
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  19. 59
  20. 60

    Deconvolution of expression microarray data reveals 131I-induced responses otherwise undetected in thyroid tissue. by Britta Langen, Nils Rudqvist, Johan Spetz, Khalil Helou, Eva Forssell-Aronsson

    Published 2018-01-01
    “…In this study, we deconvolved microarray data from thyroid tissue in order to assess possible bias from mixed cell type data. …”
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