Screening of molecular markers associated with hornless traits in Qira black sheep by Wen Zhou, Lijun Zhu, Yuwei Peng, Xiaopeng Li, Xuechen Zhang, Zhipeng Han, Jingping Li, Xinyu Bai, Qifeng Gao, Ruizhi Yang, Tao Jiang, Shudong Liu

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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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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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A practical distribution pattern of α-SMA-positive carcinoma associated fibroblasts indicates poor prognosis of patients with pancreatic ductal adenocarcinoma by Bo Li, Meilong Shi, Yang Wang, Penghao Li, Xiaoyi Yin, Guoxiao Zhang, Xiaochao Kang, Huan Wang, Suizhi Gao, Kailian Zheng, Xiaohan Shi, Xiongfei Xu, Yukun Zhou, Hui Jiang, Wei Jing, Shiwei Guo, Gang Jin

“…We utilized a tissue microarray to assess the spatial intensity of α-SMA expression within the tumor microenvironment. …”
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Exposing Optimal Feature Sets for Enhancing Machine Learning Performance by Hiba Mohammed Al-Marwai, Ghaleb H. Al-Gaphari, Mohammed Mohammed Zayed

“…To evaluate the effectiveness of our approach, we conduct experiments on benchmark microarray datasets from the ADNI database. Comparative analysis is performed against six traditional single objective methods and five other existing multiobjective methods. …”
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Successful strategy of comprehensive pre-implantation genetic testing for Duchenne muscular dystrophy and chromosome balance using karyomapping and fluorescent PCR by Suchada Mongkolchaipak, Sirivipa Piyamongkol, Chutithep Teekaput, Rungthiwa Sirapat, Wanwisa Suriya, Tawiwan Pantasri, Theera Tongsong, Wirawit Piyamongkol

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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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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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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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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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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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A RNA-Seq Analysis of the Rat Supraoptic Nucleus Transcriptome: Effects of Salt Loading on Gene Expression. by Kory R Johnson, C C T Hindmarch, Yasmmyn D Salinas, YiJun Shi, Michael Greenwood, See Ziau Hoe, David Murphy, Harold Gainer

“…In addition, we compare the SON transcriptomes resolved by RNA-Seq methods with the SON transcriptomes determined by Affymetrix microarray methods in rats under the same osmotic conditions, and find that there are 6,466 genes present in the SON that are represented in both data sets, although 1,040 of the expressed genes were found only in the microarray data, and 2,762 of the expressed genes are selectively found in the RNA-Seq data and not the microarray data. …”
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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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