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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Differential gene expression analysis in patients with primary hyperhidrosis by Ting Pu, Muhammad Ameen Jamal, Muhammad Nauman Tahir, Salman Ullah, Maher Un Nisa Awan, Asif Shahzad, Faisal Mahmood

“…Based on the highest expression of ITPR2 in hyperhidrosis, it was selected for PCR amplification as well as sequencing. …”
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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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Protein-specific immune response elicited by the Shigella sonnei 1790GAHB GMMA-based candidate vaccine in adults with varying exposure to Shigella by Arlo Z. Randall, Valentino Conti, Usman Nakakana, Xiaowu Liang, Andy A. Teng, Antonio Lorenzo Di Pasquale, Melissa Kapulu, Robert Frenck, Odile Launay, Pietro Ferruzzi, Antonella Silvia Sciré, Elisa Marchetti, Christina Obiero, Jozelyn V. Pablo, Joshua Edgar, Philip Bejon, Adam D. Shandling, Joseph J. Campo, Angela Yee, Laura B. Martin, Audino Podda, Francesca Micoli

“…An ideal vaccine would provide protection against the most prevalent species, Shigella flexneri and Shigella sonnei; therefore, it could be relevant to identify common antigens. We developed a microarray containing 3,150 full-length or fragmented proteins selected across Shigella species. …”
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Expression of long non-coding RNA in patients with non-IgA mesangial proliferative glomerulonephritis by CONG Shan, SUI Wei-guo, ZOU Gui-mian, XUE Wen, LI Huan, YAN Qiang, CHEN Jie-jing, LUO Ya-dan, CHEN Huai-zhou

“…Objective To study differential expression profile of mRNA and long non-coding RNA(IncRNA) through microarray analysis between non-IgA mesangial proliferative glomerulonephritis(MsPGN) patients and the controls,and then explore the potential role of IncRNA in the pathogenesis of non-IgA MsPGN.Methods Through simple random sampling,4 patients with non-IgA MsPGN and 2 controls were selected as disease group and control group,respectively.Renal cortical tissues from two groups were collected.Total RNA was extracted,quantified and prepared to ds-cDNA through reverse transcription ds-cDNA was labeled with NimbleGen one-color DNA labeling kit and used for array hybridization.All experimental data were processed through GO analysis,Pathway analysis and the gene loci correlation analysis of mRNA and IncRNA.Some IncRNAs that were closely related to non-IgA MsPGN were screened out.Finally,part of the array results was detected by PCR to verify the reliability of array test Results By fold change filtering,4317 differentially expressed mRNAs and 3502 differentially expressed IncRNAs were screened out.Five IncRNAs were found to play potential roles in the pathogenesis of non-IgA MsPGN:AF1180924(close to coding gene FGG),AK092233(close to coding gene COL18A1),AK130579(close to coding gene CREBBP),AK023598(close to coding gene LEPR),and AK055915(close to coding gene CDC42EP3).These results provided an important basis for revealing the pathogenesis of non-IgA MsPGN.Conclusions Some IncRNAs can potentially regulate related genes and plays an important role in the pathogenesis and development of non-IgA MsPGN.…”
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Possible cross‑talk between atrial fibrillation and obstructive sleep apnea revealed by transcriptomic analysis by Xinmiao Chen, Yi Li, Yao Liu

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Using rule-based machine learning for candidate disease gene prioritization and sample classification of cancer gene expression data. by Enrico Glaab, Jaume Bacardit, Jonathan M Garibaldi, Natalio Krasnogor

“…A comparison with other benchmark microarray sample classifiers based on three diverse feature selection algorithms suggests that these evolutionary learning techniques can compete with state-of-the-art methods like support vector machines. …”
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Evaluation of gene expression classification studies: factors associated with classification performance. by Putri W Novianti, Kit C B Roes, Marinus J C Eijkemans

“…The MAQC II study on cancer classification problems has found that performance was affected by factors such as the classification algorithm, cross validation method, number of genes, and gene selection method. In this paper, we study the hypothesis that the disease under study significantly determines which method is optimal, and that additionally sample size, class imbalance, type of medical question (diagnostic, prognostic or treatment response), and microarray platform are potentially influential. …”
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An Ensemble Classification Method for High-Dimensional Data Using Neighborhood Rough Set by Jing Zhang, Guang Lu, Jiaquan Li, Chuanwen Li

“…Efficient and effective sample classification and feature selection are challenging tasks due to high dimensionality and small sample size of microarray data. …”
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The impact of the nucleosome code on protein-coding sequence evolution in yeast. by Tobias Warnecke, Nizar N Batada, Laurence D Hurst

“…We identify nucleosome positioning as a likely candidate to set up such a DNA-level selective regime and use high-resolution microarray data in yeast to compare the evolution of coding sequence bound to or free from nucleosomes. …”
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A multi-omic meta-analysis reveals novel mechanisms of insecticide resistance in malaria vectors by Sanjay C. Nagi, Victoria A. Ingham

“…This study, employing a cross-species approach, integrates RNA-Sequencing, whole-genome sequencing, and microarray data to elucidate drivers of insecticide resistance in Anopheles gambiae complex and An. funestus. …”
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Bioinformatics meets machine learning: identifying circulating biomarkers for vitiligo across blood and tissues by Qiyu Wang, Jingwei Yuan, Jingwei Yuan, Mengdi Zhang, Haiyan Jia, Hongjie Lu, Yan Wu

“…The merged microarray data were then used for WGCNA to identify modules of features genes. …”
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Exploring Flexible Penalization of Bayesian Survival Analysis Using Beta Process Prior for Baseline Hazard by Kazeem A. Dauda, Ebenezer J. Adeniyi, Rasheed K. Lamidi, Olalekan T. Wahab

“…Moreover, in microarray research, it is common to identify groupings of genes involved in the same biological pathways. …”
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Exploration of autophagy-related molecular mechanisms underlying epilepsy using multiple datasets by Yongfei Wang, Haoxuan Zeng, Chongxu Liu, Jianjun Chen, Yihong Huang, Xianju Zhou

“…Methods We analyzed GSE143272 and GSE4290 microarray datasets from the NCBI Gene Expression Omnibus database, which is established based on evaluations of peripheral blood samples. …”
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Aberrant expression of shared master-key genes contributes to the immunopathogenesis in patients with juvenile spondyloarthritis. by Lovro Lamot, Fran Borovecki, Lana Tambic Bukovac, Mandica Vidovic, Marija Perica, Kristina Gotovac, Miroslav Harjacek

“…Microarray results and bioinformatical analysis revealed 745 differentially expressed genes involved in various inflammatory processes, while qRT-PCR analysis of selected genes confirmed data universality and specificity of expression profiles in jSpA patients. …”
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Gene Expression Profiling in Organ Transplantation by Osama Ashry Ahmed Gheith

“…However, because microarray analyses are expensive and time consuming and their statistical evaluation is often very difficult, gene expression analysis using the RTPCR method is nowadays recommended. …”
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R-locus for roaned coat is associated with a tandem duplication in an intronic region of USH2A in dogs and also contributes to Dalmatian spotting. by Takeshi Kawakami, Meghan K Jensen, Andrea Slavney, Petra E Deane, Ausra Milano, Vandana Raghavan, Brett Ford, Erin T Chu, Aaron J Sams, Adam R Boyko

“…We identified a putative causal variant in this region, an 11-kb tandem duplication (11,131,835-11,143,237) characterized by sequence read coverage and discordant reads of whole-genome sequence data, microarray probe intensity data, and a duplication-specific PCR assay. …”
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Multiple colonization with S. pneumoniae before and after introduction of the seven-valent conjugated pneumococcal polysaccharide vaccine. by Silvio D Brugger, Pascal Frey, Suzanne Aebi, Jason Hinds, Kathrin Mühlemann

“…Serotypes were identified by agglutination, multiplex PCR and microarray.<h4>Principal findings</h4>Rate of multiple colonization remained stable up to three years after PCV7 introduction. …”
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Estimation of relevant variables on high-dimensional biological patterns using iterated weighted kernel functions. by Sergio Rojas-Galeano, Emily Hsieh, Dan Agranoff, Sanjeev Krishna, Delmiro Fernandez-Reyes

“…The resulting variable subsets achieved classification accuracies of 99% on Human African Trypanosomiasis, 91% on Tuberculosis, and 91% on Malaria serum proteomic profiles with fewer than 20% of variables selected. Our method scaled-up to dimensionalities of much higher orders of magnitude as shown with gene expression microarray datasets in which we obtained classification accuracies close to 90% with fewer than 1% of the total number of variables.…”
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