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. …”
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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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LIMA1-alpha staining predicts curative intent surgery response in HPV negative head and neck cancer by Xi Qiao, Johannes Routila, Mari Tienhaara, Heikki Irjala, Priyadharshini Parimelazhagan Santhi, Teemu Huusko, Linda Nissi, Ilkka Paatero, Noora Lehtinen, Juha Rantala, Toni Viljanen, Ilmo Leivo, Petri Koivunen, Anna Jouppila-Mättö, Rami Taulu, Leif Bäck, Tommy Wilkman, Eeva Haapio, Ilpo Kinnunen, Kari Kurppa, Jukka Westermarck, Sami Ventelä

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Robust molecular subgrouping and reference-free aneuploidy detection in medulloblastoma using low-depth whole genome bisulfite sequencing by Dean Thompson, Jemma Castle, Martin Sill, Stefan M. Pfister, Simon Bailey, Debbie Hicks, Steven C. Clifford, Edward C. Schwalbe

“…We further assessed and optimised reference-free aneuploidy detection using low-pass WGBS and assessed concordance with microarray-derived calls. …”
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Copula-Based Bayesian Model for Detecting Differential Gene Expression by Prasansha Liyanaarachchi, N. Rao Chaganty

“…Finally, we apply our model to <i>Escherichia coli</i> microarray data, illustrating its practical utility in gene expression analysis.…”
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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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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

“…Conclusions Our findings strengthen that CMA is a rapid and effective genetic etiology diagnosis tool for miscarriages, producing the highest chromosomal abnormality detection rate at a gestational age of 10–11+6 weeks. …”
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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

“…The classification achieved an average accuracy of 96%, demonstrating the effectiveness of the proposed approach. Feature selection using the Kruskal–Wallis and χ2 tests revealed statistically relevant genes contributing to subgroup discrimination. …”
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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

“…Transfection efficiency was confirmed via qRT-PCR in HCT116 and SW480 colon cells, and the effects of circDOCK1 on cell proliferation, migration, and invasion were assessed.ResultsMicroarray data revealed 149 significantly differentially expressed circRNAs, including 71 upregulated and 78 downregulated circRNAs, in CRC tissues. …”
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Microarray Core Detection by Geometric Restoration by Jimmy C. Azar, Christer Busch, Ingrid B. Carlbom

“…Furthermore, the algorithm is more efficient than existing methods based on the Hough transform for circle detection. The algorithm’s simplicity, accuracy, and computational efficiency allow for automated high-throughput analysis of microarray images.…”
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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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High-throughput screening of monoclonal antibodies against carbapenemases using a multiplex protein microarray platform by Sascha D. Braun, Sascha D. Braun, Martin Reinicke, Martin Reinicke, Celia Diezel, Celia Diezel, Elke Müller, Elke Müller, Katrin Frankenfeld, Thomas Schumacher, Hugo Arends, Stefan Monecke, Stefan Monecke, Ralf Ehricht, Ralf Ehricht, Ralf Ehricht

“…The array allowed simultaneous mapping of cross-reactivity, a key advantage over conventional ELISA workflows.DiscussionOur findings confirm that protein-based microarrays offer a robust, efficient platform for antibody pair selection, reducing reagent use while accelerating assay development. …”
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Possibility of the Use of Public Microarray Database for Identifying Significant Genes Associated with Oral Squamous Cell Carcinoma by Ki-Yeol Kim, In-Ho Cha

“…Most studies include insufficient samples to apply statistical methods for detecting significant gene sets. This study combined two small microarray datasets from a public database and identified significant genes associated with the progress of oral squamous cell carcinoma. …”
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Evaluating the Nuclear Reaction Optimization (NRO) Algorithm for Gene Selection in Cancer Classification by Shahad Alkamli, Hala Alshamlan

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FEATURE SELECTION IN THE TASK OF MEDICAL DIAGNOSTICS ON MICROARRAY DATA by N. G. Zagoruiko, O. A. Kutnenko, I. A. Borisova, V. V. Dyubanov, D. A. Levanov, O. A. Zyranov

“…The high efficiency of the algorithm is illustrated by results of solving the task of disease recognition on a microarray dataset.…”
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Systematic spatial bias in DNA microarray hybridization is caused by probe spot position-dependent variability in lateral diffusion. by Doris Steger, David Berry, Susanne Haider, Matthias Horn, Michael Wagner, Roman Stocker, Alexander Loy

“…Numerical simulations reveal a strong influence of microarray well geometry on the spatial bias.<h4>Conclusions</h4>Reciprocal adjustment of the size of the microarray hybridization chamber to the area of surface-bound probes is a simple and effective measure to minimize or eliminate the diffusion-based bias, resulting in increased uniformity and accuracy of quantitative DNA microarray hybridization.…”
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Photopolymerization as an innovative detection technique for low-density microarrays by Laura R. Kuck, Amber W. Taylor

“…One limitation that accounts in part for the scarcity of commercially available diagnostic microarrays is the expense associated with fluorescence detection. …”
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Oral Bacteria of Children with Turner Syndrome by Gülcan Ünsal, Nursen Topçuoğlu, Yeliz Güven, Şükran Poyrazoğlu, Güven Külekçi, Oya Aktören

“…Plaque index and gingival index levels were significantly higher in the Turner group and dft was significantly higher in the control group (p<0.05). As a result, microarray analysis, Prevotella intermedia, Fusobacterium nucleatum, Eikenella corrodens, Aggregatibacter actinomycetemcomitans, Actinomyces viscosus were detected at high levels in the Turner group (p<0.05).Conclusion:Besides dental and craniofacial anomalies, clinicians should be alert to the early diagnosis and treatment of periodontal problems in patients with TS.…”
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Navigating the microarray landscape: a comprehensive review of feature selection techniques and their applications by Fangling Wang, Azlan Mohd Zain, Yanjie Ren, Mahadi Bahari, Azurah A. Samah, Zuraini Binti Ali Shah, Norfadzlan Bin Yusup, Rozita Abdul Jalil, Azizah Mohamad, Nurulhuda Firdaus Mohd Azmi

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A standardized fold change method for microarray differential expression analysis used to reveal genes involved in acute rejection in murine allograft models by Weichen Zhou, Yi Wang, Masayuki Fujino, Leming Shi, Li Jin, Xiao‐Kang Li, Jiucun Wang

“…We suggest that SFC can be utilized to stably and effectively detect differential gene expression and to explore microarray data in further studies.…”
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