GTI: a novel algorithm for identifying outlier gene expression profiles from integrated microarray datasets. by John Patrick Mpindi, Henri Sara, Saija Haapa-Paananen, Sami Kilpinen, Tommi Pisto, Elmar Bucher, Kalle Ojala, Kristiina Iljin, Paula Vainio, Mari Björkman, Santosh Gupta, Pekka Kohonen, Matthias Nees, Olli Kallioniemi

“…BACKGROUND: Meta-analysis of gene expression microarray datasets presents significant challenges for statistical analysis. …”
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Microarray Profiling of Vaccination-Induced Antibody Responses to SARS-CoV-2 Variants of Interest and Concern by Julia Svetlova, Dmitry Gustin, Valentin Manuvera, Dmitriy Shirokov, Varvara Shokina, Kirill Prusakov, Konstantin Aldarov, Daria Kharlampieva, Daria Matyushkina, Julia Bespyatykh, Anna Varizhuk, Vassili Lazarev, Tatiana Vedekhina

Subjects: “…microarrays…”
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Strategy to discover full-length amyloid-beta peptide ligands using high-efficiency microarray technology by Clelia Galati, Natalia Spinella, Lucio Renna, Danilo Milardi, Francesco Attanasio, Michele Francesco Maria Sciacca, Corrado Bongiorno

“…Here, we show the combination of high-efficiency slides (HESs) with peptide microarrays as a promising tool for identifying small peptides that bind Aβ monomers. …”
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Microarray-based identification of antigenic variants of foot-and-mouth disease virus: a bioinformatics quality assessment by Domingo Esteban, Ortíz Angel R, Abia David, Perales Celia, Martín Verónica, Briones Carlos

“…Recently, a FMDV microarray was described to detect simultaneously the seven FMDV serotypes. …”
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Production of endoglin-specific heavy chain antibody fragments (VHHs) microarrays for whole-cell SPR imaging by Milagros Quintana, Jose R. Espinoza, Yoann Roupioz

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A Machine Learning Pipeline for Cancer Detection on Microarray Data: The Role of Feature Discretization and Feature Selection by Adara Nogueira, Artur Ferreira, Mário Figueiredo

“…Early disease detection using microarray data is vital for prompt and efficient treatment. …”
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A microarray data analysis investigating the pathogenesis and potential biomarkers of autophagy and ferroptosis in intervertebral disc degeneration by Wenhao Kuang, Cong Jiang, Cheng Yu, Jinwei Hu, Yang Duan, Zhong Chen

“…The current study used microarray data to investigate the pathogenesis of IDD and potential biomarkers related to autophagy and ferroptosis in IDD.Methods: Differentially expressed genes (DEGs) were identified by analyzing the mRNA and miRNA expression profiles of IDD patients from the Gene Expression Omnibus (GEO). …”
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Bioinformatics analysis of differentially expressed genes in subchondral bone in early experimental osteoarthritis using microarray data by Zhao Wang, Yong Ji, Hong-wei Bao

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Retrospective screening of serum IgG glycosylation biomarker for primary Sjögren’s syndrome using lectin microarray by Siting Li, Xiaoli Zeng, Shiyi Tang, Xi Li, Guoyuan Zhang, Mengtao Li, Xiaofeng Zeng, Chaojun Hu

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Differentially profiling the low-expression transcriptomes of human hepatoma using a novel SSH/microarray approach by Lee Yung-Lin, Lee Yun-Shien, Pan Yi-Shin, Lee Wei-Chen, Hsieh Sen-Yung

“…</p> <p>Results</p> <p>We modified the previous combination of SSH and microarray methods by directly using the subtracted amplicons as targets to hybridize the pre-made cDNA microarrays (named as "SSH/microarray"). mRNA prepared from three pairs of hepatoma and non-hepatoma liver tissues was subjected to the SSH/microarray assays, as well as directly to regular cDNA microarray assays for comparison. …”
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Evaluation of the self-administration potential of high-density microarray patches to human skin: A preliminary study by B. Baker, E. Hacker, G. Siller, M. Lee, N. Mursaliyev, A. Forster

Subjects: “…microarray patch…”
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Identification of key genes effective in tolerance to drought stress in rice through meta-analysis of microarray data by Sedigheh Soltanpour, Alireza Tarinejad, Karim Hasanpur, Mohammad Majidi

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Genome-wide association analysis of time to heading and maturity in bread wheat using 55K microarrays by Yindeng Ding, Hui Fang, Yonghong Gao, Guiqiang Fan, Xiaolei Shi, Shan Yu, Sunlei Ding, Tianrong Huang, Wei Wang, Jikun Song

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The Application of Bi-clustering and Bayesian Network for Gene Sets Network Construction in Breast Cancer Microarray Data by Ahmad Sohrabi, Neda Saraygord-Afshari, Masoud Roudbari

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A generally applicable validation scheme for the assessment of factors involved in reproducibility and quality of DNA-microarray data by Albers Casper J, den Hengst Chris D, Larsen Rasmus, Kramer Naomi E, Karsens Harma A, Baerends Richard JS, de Jong Anne, van Hijum Sacha AFT, Kok Jan, Kuipers Oscar P

“…<p>Abstract</p> <p>Background</p> <p>In research laboratories using DNA-microarrays, usually a number of researchers perform experiments, each generating possible sources of error. …”
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Identification of Prognostic Biomarkers by Combined mRNA and miRNA Expression Microarray Analysis in Pancreatic Cancer by Bin Liu, Hai Yang, Leila Taher, Axel Denz, Robert Grützmann, Christian Pilarsky, Georg F. Weber

“…We used data from three mRNA microarray datasets and a microRNA dataset (GSE16515, GSE15471, GSE28735, and GSE41372) to identify potential key genes. …”
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Correction: Microarray Analyses of Glucocorticoid and Vitamin D3 Target Genes in Differentiating Cultured Human Podocytes. by Xiwen Cheng, Xuan Zhao, Simran Khurana, Leslie A. Bruggeman, Hung-Ying Kao

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Identification of the effect of lycopene on the inhibition of yellow fever-causing flavivirus by studying microarray gene expression data by Gholamreza Dadashi Oranj

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Microarray Approach Combined with ddPCR: An Useful Pipeline for the Detection and Quantification of Circulating Tumour DNA Mutations by Silvia Galbiati, Francesco Damin, Lucia Ferraro, Nadia Soriani, Valentina Burgio, Monica Ronzoni, Luca Gianni, Maurizio Ferrari, Marcella Chiari

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Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously by Steven M. Foltz, Casey S. Greene, Jaclyn N. Taroni

“…An evaluation of normalization methods shows that it is possible to combine microarray and RNA-seq data for machine learning applications.…”
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