A Comparative Analysis of Swarm Intelligence Techniques for Feature Selection in Cancer Classification by Chellamuthu Gunavathi, Kandasamy Premalatha

“…Feature selection in cancer classification is a central area of research in the field of bioinformatics and used to select the informative genes from thousands of genes of the microarray. …”
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Fabrication of DNA Microarrays Using Unmodified Oligonucleotide Probes by Douglas Ruben Call, Darrell P. Chandler, Fred Brockman

“…Our method provides a cost-effective alternative to conventional attachment strategies that is particularly suitable for genotyping PCR products with nucleic acid microarrays.…”
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Microarray-Based Cancer Diagnosis with Artificial Neural Networks by Markus Ringnér, Carsten Peterson

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Listen to genes: dealing with microarray data in the frequency domain. by Jianfeng Feng, Dongyun Yi, Ritesh Krishna, Shuixia Guo, Vicky Buchanan-Wollaston

“…<h4>Background</h4>We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes.…”
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Fast Spot Locating for Low-Density DNA Microarray by MinGin Kim, Jongwon Kim, Sun-Hee Kim, Jong-Dae Kim

“…Low-density DNA microarrays are crucial in molecular diagnostics due to their cost-effectiveness and high sensitivity. …”
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RETRACTED ARTICLE: Multi-stage biomedical feature selection extraction algorithm for cancer detection by Ismail Keshta, Pallavi Sagar Deshpande, Mohammad Shabaz, Mukesh Soni,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

“…Early cancer detection is greatly aided by machine learning and artificial intelligence (AI) to gene microarray data sets (microarray data). Despite this, there is a significant discrepancy between the number of gene features in the microarray data set and the number of samples. …”
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An efficient leukemia prediction method using machine learning and deep learning with selected features. by Mahwish Ilyas, Muhammad Ramzan, Mohamed Deriche, Khalid Mahmood, Anam Naz

“…The suggested work predicts and classifies leukemia subtypes in gene data CuMiDa (GSE9476) using feature selection and ML techniques. The Curated Microarray Database (CuMiDa) collected 64 samples representing five classes of leukemia genes out of 22283 genes. …”
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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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Phenotype microarray-based assessment of metabolic variability in plant protoplasts by Alice Checcucci, Francesca Decorosi, Giulia Alfreducci, Roberto Natale, Agnese Bellabarba, Stefano Biricolti, Donatella Paffetti, Alessio Mengoni, Carlo Viti

“…Conclusions The standardized high-throughput system developed was effective for the metabolic characterization of plant protoplasts. …”
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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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Monitoring of Representational Difference Analysis Subtraction Procedures by Global Microarrays by T. Andersson, P. Unneberg, P. Nilsson, J. Odeberg, J. Quackenbush, J. Lundeberg

“…The compromise between focusing on only the important genes in certain cellular processes and achieving a complete picture is critical for the selection of strategy. We demonstrate how global microarray technology can be used for the exploration of the differentially expressed genes extracted through representational difference analysis (RDA). …”
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Inflammatory Pathways in Parkinson’s Disease; A BNE Microarray Study by Pascal. F. Durrenberger, Edna Grünblatt, Francesca S. Fernando, Camelia Maria Monoranu, Jordan Evans, Peter Riederer, Richard Reynolds, David T. Dexter

“…The main focus of PD research is to better understand substantia nigra homeostasis disruption, particularly in relation to the wide-spread deposition of the aberrant protein α-synuclein. Microarray technology contributed towards PD research with several studies to date and one gene, ALDH1A1 (Aldehyde dehydrogenase 1 family, member A1), consistently reappeared across studies including the present study, highlighting dopamine (DA) metabolism dysfunction resulting in oxidative stress and most probably leading to neuronal cell death. …”
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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

“…For this purpose, the proposed research focused on analyzing and identifying effective feature selection algorithms. A novel framework is proposed which utilizes different feature selection methods from filters, wrappers, and embedded algorithms. …”
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Consensus PCR and Microarray for Diagnosis of the Genus Staphylococcus, Species, and Methicillin Resistance by S. Hamels, J.-L. Gala, S. Dufour, P. Vannuffel, N. Zammatteo, J. Remacle

“…Products were then identified on a glass array. The microarray contained five selective DNA capture probes for the simultaneous and differential identification of the five most clinically relevant staphylococcal species (S. aureus, S. epidermidis, S. haemolyticus, S. hominis, and S. saprophyticus), while a consensus capture probe could detect all femAsequences, allowing the identification of the genus Staphylococcus. …”
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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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Implementation of NGS and SNP microarrays in routine forensic practice: opportunities and barriers by Sharlize Pedroza Matute, Sasitaran Iyavoo

“…NGS enables STR sequencing and SNP typing with enhanced discriminatory power, better performance with degraded DNA, and improved mixture deconvolution. Conversely, SNP microarrays offer a cost-effective solution for extended kinship testing, Forensic Investigative Genetic Genealogy (FIGG), and phenotypic prediction, though they are less effective with low-quality samples and DNA mixtures. …”
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Discovery and mechanism of anti-hypertensive effect of a novel tripeptide (SYP) from medicinal fungus Ganoderma lingzhi by Qiang Wu, Feijun Luo, Jia Huang, Ping Huang, Yongnan Liu, Xiaoling Wang, Gaoqiang Liu

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Application of Chromosome Microarray in Diagnosis of Amniotic Fluid in Older Pregnant Women by Guangting Lu, Weiwu Liu, Chao Ou

“…Background: To improve the detection rate of chromosome abnormalities in fetuses and to reduce the birth defects rate in elderly pregnant women using chromosome karyotype analysis combined with the chromosome microarray analysis (CMA) technique. Methods: Overall, 210 elderly pregnant women with singleton pregnancies aged between 16 and 30 weeks (mean gestational age, 19.19 weeks) and 35 and 47 years (mean age, 38.08 years) were selected from January 1, 2020 to June 1, 2021 in the Eugenics Genetics Department of Yulin Maternal and Child Health Hospital. …”
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Microarray integrated spatial transcriptomics (MIST) for affordable and robust digital pathology by Juwayria, Priyansh Shrivastava, Kaustar Yadav, Sourabh Das, Shubham Mittal, Sunil Kumar, Deepali Jain, Prabhat Singh Malik, Ishaan Gupta

“…To address these issues, we propose Microarray Integrated Spatial Transcriptomics (MIST), combining conventional tissue microarray (TMA) with Visium, using laser-cutting and 3D printing to enhance slide throughput. …”
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Gene expression analysis of ABC transporter family in breast tumors: relationship with chemotherapy effect and disease prognosis by M. M. Tsyganov, M. K. Ibragimova, A. M. Pevzner, K. A. Gaptulbarova, E. Yu. Garbukov, Е. М. Slonimskaya, E. A. Usynin, N. V. Litviakov

“…RNA was isolated from paired samples of tumor tissue before and after NAC. A microarray study of all tumor samples was performed on ClariomТМ S Assay, human microarrays. …”
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