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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Microarray Data Analysis: From Hypotheses to Conclusions Using Gene Expression Data by Nicola J. Armstrong, Mark A. van de Wiel

“…We review several commonly used methods for the design and analysis of microarray data. To begin with, some experimental design issues are addressed. …”
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A Novel Ensemble Feature Selection Technique for Cancer Classification Using Logarithmic Rank Aggregation Method by Hüseyin Öztoprak, Hüseyin Güney

“…Recent studies have shown that ensemble feature selection (EFS) has achieved outstanding performance in microarray data classification. …”
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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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A tailored lectin microarray for rapid glycan profiling of therapeutic monoclonal antibodies by Shen Luo, Baolin Zhang

“…In this study, we introduce a custom-designed lectin microarray featuring nine distinct lectins: rPhoSL, rOTH3, RCA120, rMan2, MAL_I, rPSL1a, PHAE, rMOA, and PHAL. …”
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High reproducibility using sodium hydroxide-stripped long oligonucleotide DNA microarrays by Zhiyuan Hu, Melissa Troester, Charles M. Perou

“…In addition, when there is limited availability of mRNA from tissue sources, RNA amplification can and is being used to produce sufficient quantities of cRNA for microarray hybridization. Taking advantage of the selective degradation of RNA under alkaline conditions, we have developed a method to “strip” glass-based oligonucleotide microarrays that use fluorescent RNA in the hybridization, while leaving the DNA oligonucleotide probes intact and usable for a second experiment. …”
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CRISPR screens and lectin microarrays identify high mannose N-glycan regulators by C. Kimberly Tsui, Nicholas Twells, Jenni Durieux, Emma Doan, Jacqueline Woo, Noosha Khosrojerdi, Janiya Brooks, Ayodeji Kulepa, Brant Webster, Lara K. Mahal, Andrew Dillin

“…We used CRISPR screens to uncover the expanded network of genes controlling high mannose levels, followed by lectin microarrays to fully measure the complex effect of select regulators on glycosylation globally. …”
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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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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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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

“…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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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

“…This retrospective cohort study utilizes chromosomal microarray analysis (CMA) to systematically investigate chromosomal abnormalities associated with early pregnancy loss. …”
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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

“…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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Machine learning identification of molecular targets for medulloblastoma subgroups using microarray gene fingerprint analysis by Alicia Reveles-Espinoza, Ulises Villela, Edgar Hernandez-Martinez, Isaac Chairez, Sergio Juárez-Méndez, J. Casanova-Moreno, Ma. del Pilar Eguía-Aguilar, Luis Figueroa-Yáñez, Adriana Vallejo-Cardona, Iván Salgado

“…An artificial neural network (ANN) model trained on microarray gene expression data determined minimal gene combinations for each subgroup. …”
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Circular RNA microarray expression profile and potential function of circDOCK1 in colorectal cancer by Guojing Zhang, Xiaoyan Wu, Hongmin Fu, Daqing Sun

“…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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