Cell-binding microarray application in diagnosis of hairy cell leukemia by A. N. Khvastunova, L. S. Al-Radi, N. M. Kapranov, O. S. Fedyanina, L. A. Gorgidze, S. A. Lugovskaya, E. V. Naumova, U. L. Dzhulakyan, A. V. Filatov, F. I. Ataullakhanov, S. A. Kuznetsova

“…We describe an application of a cell-binding microarray – to parallel study of morphology, tartrate-resistant acid phosphatase activity and detection of surface markers on peripheral blood lymphocytes of 90  atients with suspected hairy cell leukemia (HCL). …”
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Drug and cell type-specific regulation of genes with different classes of estrogen receptor beta-selective agonists. by Sreenivasan Paruthiyil, Aleksandra Cvoro, Xiaoyue Zhao, Zhijin Wu, Yunxia Sui, Richard E Staub, Scott Baggett, Candice B Herber, Chandi Griffin, Mary Tagliaferri, Heather A Harris, Isaac Cohen, Leonard F Bjeldanes, Terence P Speed, Fred Schaufele, Dale C Leitman

“…U2OS cells stably transfected with ERalpha or ERbeta were treated with E(2) or the ERbeta-selective compounds for 6 h. Microarray data demonstrated that ERB-041, MF101 and liquiritigenin were the most ERbeta-selective agonists compared to estradiol, followed by nyasol and then diarylpropionitrile. …”
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A Novel Feature Selection Method for Classification of Medical Data Using Filters, Wrappers, and Embedded Approaches by Saba Bashir, Irfan Ullah Khattak, Aihab Khan, Farhan Hassan Khan, Abdullah Gani, Muhammad Shiraz

“…Feature selection is the process of identifying the most relevant features from the given data having a large feature space. …”
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Enhanced leukemia prediction using hybrid ant colony and ant lion optimization for gene selection and classification by Santhakumar D, Gnanajeyaraman Rajaram, Elankavi R, Viswanath J, Govindharaj I, Raja J

“…Gene selection plays a crucial role in the pre-processing of microarray data, aiming to identify a small set of genes that enhances classification accuracy and reduces costs. …”
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Genetic Comparison and Selection of Reproductive and Growth-Related Traits in Qinchuan Cattle and Two Belgian Cattle Breeds by Xiaopeng Li, Peng Niu, Xueyan Wang, Fei Huang, Jieru Wang, Huimin Qu, Chunmei Han, Qinghua Gao

“…These findings provide valuable molecular markers for enhancing reproductive efficiency, growth, and meat production through genetic selection and selective breeding strategies.…”
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Mapping quantitative trait loci regions associated with Marek’s disease on chicken autosomes by means of selective DNA pooling by Ehud Lipkin, Jacqueline Smith, Morris Soller, David W. Burt, Janet E. Fulton

“…Allele substitution effects were calculated based on both pooled SNP microarray genotypes, and individual genotypes of QTLRs markers. …”
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Generation of Antigen Microarrays to Screen for Autoantibodies in Heart Failure and Heart Transplantation. by Andrzej Chruscinski, Flora Y Y Huang, Albert Nguyen, Jocelyn Lioe, Laura C Tumiati, Stella Kozuszko, Kathryn J Tinckam, Vivek Rao, Shannon E Dunn, Michael A Persinger, Gary A Levy, Heather J Ross

“…We first demonstrated that our antigen microarray technique displayed enhanced sensitivity to detect autoantibodies compared to the traditional ELISA method. …”
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Comparative Microarray Analysis of Proliferating and Differentiating Murine ENS Progenitor Cells by Peter Helmut Neckel, Roland Mohr, Ying Zhang, Bernhard Hirt, Lothar Just

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RNA Amplification Results in Reproducible Microarray Data with Slight Ratio Bias by László G. Puskás, Ágnes Zvara, László Hackler, Paul Van Hummelen

“…Microarray expression analysis demands large amounts of RNA that are often not available. …”
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ZODET: software for the identification, analysis and visualisation of outlier genes in microarray expression data. by Daniel L Roden, Gavin W Sewell, Anna Lobley, Adam P Levine, Andrew M Smith, Anthony W Segal

“…Here we describe a graphical software package (z-score outlier detection (ZODET)) that enables identification and visualisation of gross abnormalities in gene expression (outliers) in individuals, using whole genome microarray data. …”
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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

“…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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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

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

“…Evaluation of products of conception (POC) is very important to detect chromosomal abnormalities associated with RPL. …”
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Reuse of cDNA microarrays hybridized with cRNA by stripping with RNase H by Haoxiang Wu, James A Bynum, Salomon Stavchansky, Phillip D. Bowman

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

“…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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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

“…<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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Clinical Findings Associated with a De Novo Partial Trisomy 10p11.22p15.3 and Monosomy 7p22.3 Detected by Chromosomal Microarray Analysis by Omid Kohannim, Jane Peredo, Katrina M. Dipple, Fabiola Quintero-Rivera

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Enucleation-Induced Rat Adrenal Gland Regeneration: Expression Profile of Selected Genes Involved in Control of Adrenocortical Cell Proliferation by Marianna Tyczewska, Marcin Rucinski, Agnieszka Ziolkowska, Marta Szyszka, Marcin Trejter, Anna Hochol-Molenda, Krzysztof W. Nowak, Ludwik K. Malendowicz

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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

“…Abstract Background Chromosomal microarray analysis (CMA) is being increasingly used to reveal the genetic causes of miscarriage. …”
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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

“…Here, we intend to investigate the significance of Chromosomal Microarray Analysis (CMA) in the prenatal diagnosis of definite FGR. …”
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