Generalizability of machine learning models for diabetes detection a study with nordic islet transplant and PIMA datasets by Dinesh Chellappan, Harikumar Rajaguru

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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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In-depth immunochemical characterization of the serum antibody response using a dual-titration microspot assay by Ágnes Kovács, Ágnes Kovács, Zoltán Hérincs, Krisztián Papp, Jakub Zbigniew Kaczmarek, Daniel Nyberg Larsen, Daniel Nyberg Larsen, Pernille Stage, László Bereczki, Eszter Ujhelyi, Tamás Pfeil, Tamás Pfeil, József Prechl

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Identification of three small nucleolar RNAs (snoRNAs) as potential prognostic markers in diffuse large B‐cell lymphoma by Mei‐wei Li, Feng‐xiang Huang, Zu‐cheng Xie, Hao‐yuan Hong, Qing‐yuan Xu, Zhi‐gang Peng

“…Results Twelve prognosis‐correlated snoRNAs were selected from the DLBCL patient cohort of microarray profiles, and a three‐snoRNA signature consisting of SNORD1A, SNORA60, and SNORA66 was constructed. …”
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Effects of oxidized phospholipids on gene expression in RAW 264.7 macrophages: a microarray study. by Daniel Koller, Hubert Hackl, Juliane Gertrude Bogner-Strauß, Albin Hermetter

“…In this study we present the effects of 1-palmitoyl-2-glutaroyl-sn-glycero-3-phosphocholine (PGPC) and 1-palmitoyl-2-(5-oxovaleroyl)-sn-glycero-3-phosphocholine (POVPC) on gene expression in RAW 264.7 macrophages using cDNA microarrays. …”
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DurdusTools—An Online Genetic Distance Calculation Tool for Efficient Variety Testing in Durum Wheat (<i>Triticum turgidum</i> L. subsp. <i>durum</i> (Desf.) Husn.) by Alexandra Ribarits, Svenja Bomers, Tadej Zerak, Oliver Alber, Jakob Seereiter, Antonio Escolano García, Ana Lázaro Somoza, Anna Pia Maria Giulini, Ferenc Somogyi, Sándor Kőrösi, Jutta Taferner-Kriegl

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Method for Printing Functional Protein Microarrays by James B. Delehanty, Frances S. Ligler

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Using effective subnetworks to predict selected properties of gene networks. by Gemunu H Gunaratne, Preethi H Gunaratne, Lars Seemann, Andrei Török

“…Steady state measurements of these influence networks can be obtained from DNA microarray experiments. However, since they contain a large number of nodes, the computation of influence networks requires a prohibitively large set of microarray experiments. …”
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Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization by Sumet Mehta, Fei Han, Muhammad Sohail, Bhekisipho Twala, Asad Ullah, Fasee Ullah, Arfat Ahmad Khan, Qinghua Ling

Subjects: “…Microarray gene selection…”
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A two stage grading approach for feature selection and classification of microarray data using Pareto based feature ranking techniques: A case study by Rasmita Dash

“…High dimensional search space in microarray data with large number of genes and few dozen of samples increases the complexity of analysis of such databases. …”
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Microarray analysis of the effects of Acthar Gel versus methylprednisolone in a model of focal segmental glomerulosclerosis in female rats by Kyle Hayes, Dale Wright

“…On Day 56, animals were sacrificed, and RNA samples of kidney cortex tissue were analyzed using microarrays. Compared with control, Acthar significantly decreased the expression of more genes related to inflammation, immune function, and fibrosis than MP. …”
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Microarray-Based Cancer Diagnosis with Artificial Neural Networks by Markus Ringnér, Carsten Peterson

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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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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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Xq12q13.2 duplication detected in a child in selective exome screening by A. A. Dokshukina, Je. Shubina, D. N. Maslennikov, I. O. Sadelov, E. R. Tolmacheva, S. V. Ionushene, T. A. Bairova, L. V. Rychkova, D. Yu. Trofimov, D. N. Degtyarev

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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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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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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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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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