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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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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Enucleation-Induced Rat Adrenal Gland Regeneration: Expression Profile of Selected Genes Involved in Control of Adrenocortical Cell Proliferation by Marianna Tyczewska, Marcin Rucinski, Agnieszka Ziolkowska, Marta Szyszka, Marcin Trejter, Anna Hochol-Molenda, Krzysztof W. Nowak, Ludwik K. Malendowicz

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Mechanism-based screen for G1/S checkpoint activators identifies a selective activator of EIF2AK3/PERK signalling. by Simon R Stockwell, Georgina Platt, S Elaine Barrie, Georgia Zoumpoulidou, Robert H Te Poele, G Wynne Aherne, Stuart C Wilson, Peter Sheldrake, Edward McDonald, Mathilde Venet, Christelle Soudy, Frédéric Elustondo, Laurent Rigoreau, Julian Blagg, Paul Workman, Michelle D Garrett, Sibylle Mittnacht

“…Our work therefore identifies CCT020312 as a novel small molecule chemical tool for the selective activation of EIF2A-mediated translation control with utility for proof-of-concept applications in EIF2A-centered therapeutic approaches, and as a chemical starting point for pathway selective agent development. …”
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Improving machine learning detection of Alzheimer disease using enhanced manta ray gene selection of Alzheimer gene expression datasets by Zahraa Ahmed, Mesut Çevik

“…However, the late enriched understanding of the genetic underpinnings of AD has been made possible due to recent advancements in data mining analysis methods, machine learning, and microarray technologies. However, the “curse of dimensionality” caused by the high-dimensional microarray datasets impacts the accurate prediction of the disease due to issues of overfitting, bias, and high computational demands. …”
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THE VALIDATION OF THE RESULTS OF MICROARRAY STUDIES OF ASSOCIATION BETWEEN GENE POLYMORPHISMS AND THE FREQUENCY OF RADIATION EXPOSURE MARKERS by M. V. Khalyuzova, N. V. Litvyakov, A. E. Sazonov, Ye. N. Albakh, D. S. Isubakova, A. B. Karpov, R. M. Takhauov

“…The results from the selective validation research into the association between genetic polymorphisms and the frequency of cytogenetic abnormalities on a large independent sample are analyzed. …”
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Themis2/ICB1 is a signaling scaffold that selectively regulates macrophage Toll-like receptor signaling and cytokine production. by Matthew J Peirce, Matthew Brook, Nicholas Morrice, Robert Snelgrove, Shajna Begum, Alessandra Lanfrancotti, Clare Notley, Tracy Hussell, Andrew P Cope, Robin Wait

“…<h4>Background</h4>Thymocyte expressed molecule involved in selection 1 (Themis1, SwissProt accession number Q8BGW0) is the recently characterised founder member of a novel family of proteins. …”
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Microarray analysis of virulence gene profiles in Salmonella serovars from food/food animal environment by Wen Zou, Sufian F Al-Khaldi, William S Branham, Tao Han, James C Fuscoe, Jing Han, Steven L Foley, Joshua Xu, Hong Fang, Carl E Cerniglia, Rajesh Nayak

“…Methodology:  The spotted array consisted of 69 selected Salmonella-specific virulence gene probes (65bp each).  …”
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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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Discovery of possible gene relationships through the application of self-organizing maps to DNA microarray databases. by Rocio Chavez-Alvarez, Arturo Chavoya, Andres Mendez-Vazquez

“…DNA microarrays and cell cycle synchronization experiments have made possible the study of the mechanisms of cell cycle regulation of Saccharomyces cerevisiae by simultaneously monitoring the expression levels of thousands of genes at specific time points. …”
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Molecular sub-classification of renal epithelial tumors using meta-analysis of gene expression microarrays. by Thomas Sanford, Paul H Chung, Ariel Reinish, Vladimir Valera, Ramaprasad Srinivasan, W Marston Linehan, Gennady Bratslavsky

“…<h4>Experimental design</h4>A search of publicly available databases was performed to identify microarray datasets with multiple histologic sub-types of renal cortical neoplasms. …”
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Quantitative and Qualitative Variations in TILs in Risk Stratification and Patient Selection for Neoadjuvant Chemotherapy of the Luminal B and Triple-Negative Breast Cancer Immunop... by Ana Car Peterko, Koraljka Rajković Molek, Anita Savić Vuković, Tamara Gulić, Petra Valković Zujić, Eleonora Cini Tešar, Damir Juranić, Aleksandra Pirjavec Mahić, Franjo Lovasić, Gordana Đorđević, Manuela Avirović

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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

“…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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Carbohydrate Microarrays Identify Blood Group Precursor Cryptic Epitopes as Potential Immunological Targets of Breast Cancer by Denong Wang, Jin Tang, Shaoyi Liu, Jiaoti Huang

“…Using carbohydrate microarrays, we explored potential natural ligands of antitumor monoclonal antibody HAE3. …”
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Gene markers of fracture healing in early stage and the regulatory mechanism during the process using microarray analysis by Chengxue Wang, Baochang Qi, Lei Tan, Jieping Cheng

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Combining gene expression microarrays and Mendelian randomization: exploring key immune-related genes in multiple sclerosis by Shuangfeng Ding, Yunyun Zhang, Yunzhe Tang, Ying Zhang, Mingyuan Liu

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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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IDENTIFYING IMPORTANT GENES IN OVARIAN CANCER FROM HIGH-DIMENSIONAL MICROARRAY DATA USING SIFS-CART METHOD by Ni Kadek Emik Sapitri, Umu Sa'adah, Nur Shofianah

“…Ovarian cancer can be identified from microarray data using machine learning. Many studies only focus on improving the machine learning classification algorithms to achieve higher performance. …”
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