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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Transfer learning for accelerated failure time model with microarray data by Yan-Bo Pei, Zheng-Yang Yu, Jun-Shan Shen

“…Abstract Background In microarray prognostic studies, researchers aim to identify genes associated with disease progression. …”
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BIMSSA: enhancing cancer prediction with salp swarm optimization and ensemble machine learning approaches by Pinakshi Panda, Sukant Kishoro Bisoy, Amrutanshu Panigrahi, Abhilash Pati, Bibhuprasad Sahu, Zheshan Guo, Haipeng Liu, Prince Jain

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RETRACTED ARTICLE: Multi-stage biomedical feature selection extraction algorithm for cancer detection by Ismail Keshta, Pallavi Sagar Deshpande, Mohammad Shabaz, Mukesh Soni, Mohit kumar Bhadla, Yasser Muhammed

“…Abstract Cancer is a significant cause of death worldwide. Early cancer detection is greatly aided by machine learning and artificial intelligence (AI) to gene microarray data sets (microarray data). …”
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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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Optimization based tumor classification from microarray gene expression data. by Onur Dagliyan, Fadime Uney-Yuksektepe, I Halil Kavakli, Metin Turkay

“…<h4>Background</h4>An important use of data obtained from microarray measurements is the classification of tumor types with respect to genes that are either up or down regulated in specific cancer types. …”
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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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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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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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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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Robust Microarray Meta-Analysis Identifies Differentially Expressed Genes for Clinical Prediction by John H. Phan, Andrew N. Young, May D. Wang

“…Combining multiple microarray datasets increases sample size and leads to improved reproducibility in identification of informative genes and subsequent clinical prediction. …”
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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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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 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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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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