Integrative Bioinformatics Analysis Unravel the Association between Intracerebral Hemorrhage and Cellular Apoptosis through Immune Infiltration by Pandi Chen, Gengfan Ye, Jia Li, Kuan Feng, Guangyao Zhu, Maosong Chen, Wei Chen

“…Key genes were identified through least absolute shrinkage and selection operator regression after model validation. …”
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Identification of G1-regulated genes in normally cycling human cells. by Maroun J Beyrouthy, Karen E Alexander, Amy Baldwin, Michael L Whitfield, Hank W Bass, Dan McGee, Myra M Hurt

“…<h4>Methodology and findings</h4>We used a robotic mitotic shake-off apparatus to select cells in late mitosis for genome-wide gene expression studies. …”
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Clustering, Pathway Enrichment, and Protein-Protein Interaction Analysis of Gene Expression in Neurodevelopmental Disorders by Ruchi Yadav, Prachi Srivastava

“…Finally, 60 genes were selected on the basis of coexpression analysis. Further pathway analysis was done using the Metascape tool, and the biological process was studied using gene ontology database. …”
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Expression of Genes Related to Germ Cell Lineage and Pluripotency in Single Cells and Colonies of Human Adult Germ Stem Cells by Sabine Conrad, Hossein Azizi, Maryam Hatami, Mikael Kubista, Michael Bonin, Jörg Hennenlotter, Karl-Dietrich Sievert, Thomas Skutella

“…Genome-wide comparisons with microarray analysis confirmed that different haGSC colonies exhibited gene expression heterogeneity with more or less pluripotency. …”
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The significance of long chain non-coding RNA signature genes in the diagnosis and management of sepsis patients, and the development of a prediction model by Yong Bai, Jing Gao, Yuwen Yan, Xu Zhao

“…The purpose of this study was to determine the value of Long chain non-coding RNA (LncRNA) RP3_508I15.21, RP11_295G20.2, and LDLRAD4_AS1 in the diagnosis of adult sepsis patients and to develop a Nomogram prediction model.MethodsWe screened adult sepsis microarray datasets GSE57065 and GSE95233 from the GEO database and performed differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA), and machine learning methods to find the genes by random forest (Random Forest), least absolute shrinkage and selection operator (LASSO), and support vector machine (SVM), respectively, with GSE95233 as the training set and GSE57065 as the validation set. …”
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Transcriptional Profile of Kidney from Type 2 Diabetic db/db Mice by Haojun Zhang, Tingting Zhao, Zhiguo Li, Meihua Yan, Hailing Zhao, Bin Zhu, Ping Li

“…The top 10 hub genes were selected from the constructed PPI network of DEGs, including Ccnb2 and Nr1i2, which remained largely unclear in DN. …”
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Identification of Differentially Expressed Genes and Long Noncoding RNAs Associated with Parkinson’s Disease by Lu-Mei Chi, Li-Ping Wang, Dan Jiao

“…This study aims to determine differentially expressed genes (DEGs) and long noncoding RNAs (lncRNAs) associated with Parkinson’s disease (PD) using a microarray. Methods. We downloaded the microarray data GSE6613 from the Gene Expression Omnibus, which included 105 samples. …”
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Transcriptional profiling of nitrogen fixation and the role of NifA in the diazotrophic endophyte Azoarcus sp. strain BH72. by Abhijit Sarkar, Barbara Reinhold-Hurek

“…For selected genes, differential expression was corroborated by real time RT-PCR studies.…”
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Gene expression profiles in Parkinson disease prefrontal cortex implicate FOXO1 and genes under its transcriptional regulation. by Alexandra Dumitriu, Jeanne C Latourelle, Tiffany C Hadzi, Nathan Pankratz, Dan Garza, John P Miller, Jeffery M Vance, Tatiana Foroud, Thomas G Beach, Richard H Myers

“…Single-nucleotide polymorphisms (SNPs) selected from a recent meta-analysis of PD genome-wide association studies (GWAS) were successfully genotyped in 50 out of the 53 microarray brains, allowing a targeted expression-SNP (eSNP) analysis for 52 SNPs associated with PD affection at genome-wide significance and the 189 probes from FoxO1 regulated genes. …”
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Molecular profiles of tumor contrast enhancement: A radiogenomic analysis in anaplastic gliomas by Xing Liu, Yiming Li, Zhiyan Sun, Shaowu Li, Kai Wang, Xing Fan, Yuqing Liu, Lei Wang, Yinyan Wang, Tao Jiang

“…Gene set enrichment analysis (GSEA), significant analysis of microarray, generalized linear models, and Least absolute shrinkage and selection operator algorithm were used to explore radiogenomic and prognostic signatures of AG patients. …”
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Identifying a unique chromosomal pattern to predict the gemcitabine response in patients with cholangiocarcinoma by Sutheemon Techa-ay, Sasithorn Watcharadetwittaya, Raksawan Deenonpoe, Prakasit Sa-ngiamwibool, Chanita Panwoon, Watcharin Loilome, Poramate Klanrit, Anchalee Techasen, Yaovalux Chamgramol, Manida Suksawat, Napat Armartmuntree, Thomas O’Connor, Hideyuki Saya, Malinee Thanee

“…This signature pattern could provide the knowledge to improve a predictive biomarker for GEM response, benefitting for individual CCA patient management and chemotherapeutic selection.…”
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A Transcriptional Signature of Fatigue Derived from Patients with Primary Sjögren's Syndrome. by Katherine James, Shereen Al-Ali, Jessica Tarn, Simon J Cockell, Colin S Gillespie, Victoria Hindmarsh, James Locke, Sheryl Mitchell, Dennis Lendrem, Simon Bowman, Elizabeth Price, Colin T Pease, Paul Emery, Peter Lanyon, John A Hunter, Monica Gupta, Michele Bombardieri, Nurhan Sutcliffe, Costantino Pitzalis, John McLaren, Annie Cooper, Marian Regan, Ian Giles, David Isenberg, Vadivelu Saravanan, David Coady, Bhaskar Dasgupta, Neil McHugh, Steven Young-Min, Robert Moots, Nagui Gendi, Mohammed Akil, Bridget Griffiths, UK Primary Sjögren’s Syndrome registry, Anil Wipat, Julia Newton, David E Jones, John Isaacs, Jennifer Hallinan, Wan-Fai Ng

“…Finally, gene set enrichment analysis (GSEA) was used as a feature selection technique for input into a support vector machine (SVM) classifier. …”
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Identification of Hub Biomarkers and Immune and Inflammation Pathways Contributing to Kawasaki Disease Progression with RT-qPCR Verification by Hongjun Ba, Lili Zhang, Huimin Peng, Xiufang He, Yuese Lin, Xuandi Li, Shujuan Li, Ling Zhu, Youzhen Qin, Xing Zhang, Yao Wang

“…Patients and Methods. Gene microarray data were collected from the Gene Expression Omnibus database. …”
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Immune-related gene characterization and biological mechanisms in major depressive disorder revealed based on transcriptomics and network pharmacology by Shasha Wu, Shasha Wu, Qing Jiang, Jinhui Wang, Jinhui Wang, Daming Wu, Yan Ren

“…Subsequently, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Cytoscape plugin CluGO, and Gene Set Enrichment Analysis (GSEA) were utilized to identify immune-related genes. The final selection of immune-related hub genes was determined through the least absolute shrinkage and selection operator (Lasso) regression analysis and PPI analysis. …”
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Mutation Spectrum of the ABCA4 Gene in a Greek Cohort with Stargardt Disease: Identification of Novel Mutations and Evidence of Three Prevalent Mutated Alleles by Kamakari Smaragda, Kokkinou Vassiliki, Koutsodontis George, Stamatiou Polixeni, Giatzakis Christoforos, Anastasakis Anastasios, Aslanides Ioannis Minas, Koukoula Stavrenia, Panagiotoglou Theoni, Datseris Ioannis, Tsilimbaris K. Miltiadis

“…A total of 59 patients were analyzed for ABCA4 mutations using the ABCR400 microarray and PCR-based sequencing of all coding exons and flanking intronic regions. …”
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Global gene expression profiling reveals SPINK1 as a potential hepatocellular carcinoma marker. by Aileen Marshall, Margus Lukk, Claudia Kutter, Susan Davies, Graeme Alexander, Duncan T Odom

“…Six genes identified by microarray as highly expressed in HH-HCC were confirmed by RT qPCR. …”
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Differentially expressed miR-3680-5p is associated with parathyroid hormone regulation in peritoneal dialysis patients. by Sohyun Jeong, Jung Mi Oh, Kook-Hwan Oh, In-Wha Kim

“…Total RNA from 15 patients (7 and 8 patients in the low and high iPTH groups, respectively) underwent miRNA microarray analysis, and three differentially upregulated (>2-fold change) miRNAs previously associated with human disease were selected for real-time quantitative PCR (qPCR) analysis. …”
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Identification and validation of diagnostic genes IFI44 and IRF9 in insomnia-associated autoimmune uveitis by Chao Wu, Hui Feng, Meng Tian, Baorui Chu, Xianyang Liu, Shuhao Zeng, Yakun Wang, Hong Wang, Shengping Hou, Qingfeng Liang

“…Least absolute shrinkage and selection operator regression was employed to screen for candidate biomarkers, and their diagnostic performance was evaluated using receiver operating characteristic (ROC) curves and quantitative polymerase chain reaction (qPCR). …”
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Diverse regulated cell death patterns and immune traits in kidney allograft with fibrosis: a prediction of renal allograft failure based on machine learning, single-nucleus RNA seq... by Yuqing Li, Jiandong Zhang, Xuemeng Qiu, Yifei Zhang, Jiyue Wu, Qing Bi, Zejia Sun, Wei Wang

“…A 9-gene signature, termed RCD risk score (RCDI), was constructed using the least absolute shrinkage and selection operator and multivariate Cox regression algorithms. …”
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The potential crosstalk genes and molecular mechanisms between systemic lupus erythematosus and periodontitis by Kai Zhao, Xiaolong Li, Qingmiao Zhu, Mengyu Zhu, Jinge Huang, Ting Zhao

“…Random forest (RF) and Least Absolute Shrinkage and Selection Operator (Lasso) regression were employed to identify key hub genes. …”
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