Weighted frequent gene co-expression network mining to identify genes involved in genome stability. by Jie Zhang, Kewei Lu, Yang Xiang, Muhtadi Islam, Shweta Kotian, Zeina Kais, Cindy Lee, Mansi Arora, Hui-Wen Liu, Jeffrey D Parvin, Kun Huang

“…In this study, we used a network mining algorithm to identify tightly connected gene co-expression networks that are frequently present in microarray datasets from 33 types of cancer which were derived from 16 organs/tissues. …”
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Have maternal or paternal ages any impact on the prenatal incidence of genomic copy number variants associated with fetal structural anomalies? by Marta Larroya, Marta Tortajada, Eduard Mensión, Montse Pauta, Laia Rodriguez-Revenga, Antoni Borrell

“…We conducted a non-paired case-control study (1:2 ratio) among pregnancies undergoing chromosomal microarray analysis (CMA) because of fetal ultrasound anomalies, from December 2012 to May 2020. …”
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Identification of the Exercise and Time Effects on Human Skeletal Muscle through Bioinformatics Methods by Mufang Feng, Jie Ji, Xiaoliu Li, Xinming Ye

“…To determine the effects of exercise and time on human skeletal muscle, we downloaded the microarray expression profile of GSE1832 and analyzed it to select differentially expressed genes (DEGs). …”
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Cuproptosis genes in predicting the occurrence of allergic rhinitis and pharmacological treatment. by Ting Yi

“…<h4>Results</h4>Four AR signature genes (MRPS30, CLPX, MRPL13, and MRPL53) were selected by the MCC, EPC, BottleNeck, and Closeness algorithms. …”
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Bioinformatic-based differential expression gene expressions of epithelial mesenchymal transformation in diabetic kidney disease and prediction of traditional Chinese medicine by Liu Wu, Zhou Yi, Yu Fang-ning, Zhang Ning

“…ObjectiveBased upon the bioinformatic analysis of gene chip data between patients with diabetic kidney disease （DKD） and normal controls， differentially expressed genes of epithelial mesenchymal transformation of DKD were screened for elucidating its pathogenesis and predicting the potential therapeutic Chinese medicine for DKD.MethodsGSE23338 microarray data were downloaded from gene expression omnibus， related differentially expressed genes screened by R language and differentially expressed genes analyzed by Gene Ontology， Kyoto Encyclopedia of Genes and Genomes. …”
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Cellular senescence-associated genes in rheumatoid arthritis: Identification and functional analysis. by You Ao, Qing Lan, Tianhua Yu, Zhichao Wang, Jing Zhang

“…In our study, we analyzed RA microarray data from the Gene Expression Omnibus (GEO) and focused on cellular senescence genes from the CellAge database. …”
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MicroRNA biomarkers of type 2 diabetes: A protocol for corroborating evidence by computational genomics and meta-analyses. by Hongmei Zhu, Siu-Wai Leung

“…Biologically relevant microRNAs will then be selected through genomic database corroboration. Their association with T2D is further measured by area under the curve (AUC) of receive operating characteristic (ROC). …”
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Integrated Bioinformatics Analysis of Hub Genes and Pathways in Anaplastic Thyroid Carcinomas by Xueren Gao, Jianguo Wang, Shulong Zhang

“…The aim of the present study was to identify hub genes and pathways in ATC by microarray expression profiling. Two independent datasets (GSE27155 and GSE53072) were downloaded from GEO 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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Bioinformatic identification of Single Nucleotide Polymorphisms (SNPs) in keratin-associated protein genes in alpacas (Vicugna pacos) by Deyanira Figueroa, Manuel More, Gustavo Gutiérrez, F. Abel Ponce de León

“…Of these, 35 SNPs were included in the 76K alpaca SNP microarray and 32 SNPs were confirmed in a population of 936 alpacas.…”
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Pairing of competitive and topologically distinct regulatory modules enhances patterned gene expression by Itai Yanai, L Ryan Baugh, Jessica J Smith, Casey Roehrig, Shai S Shen‐Orr, Julia M Claggett, Andrew A Hill, Donna K Slonim, Craig P Hunter

“…We used RNAi and time series, whole‐genome microarray analyses to systematically perturb and characterize components of a Caenorhabditis elegans lineage‐specific transcriptional regulatory network. …”
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Effect of Storage Temperature on Key Functions of Cultured Retinal Pigment Epithelial Cells by Lara Pasovic, Jon Roger Eidet, Berit S. Brusletto, Torstein Lyberg, Tor P. Utheim

“…Total RNA was isolated and the gene expression profile was determined using DNA microarrays. Comparison of the microarray expression values with qRT-PCR analysis of selected genes validated the results. …”
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Evaluation of LRIG1 Expression in Larynx Pathologies by Yavuz Gündoğdu, Orhan Asya, Ayşegül Gönen, Tajaddin Muradov, Selim Yiğit Erçetin, Zeliha Leyla Cinel, Ali Cemal Yumuşakhuylu

“…Patients’ data were obtained from the medical records. The tissue microarray method was used to evaluate specimens. Results: There was a statistically significant difference between the tumor differentiation, diagnosis, and the expression of LRIG1 (respectively p=0.045, p&lt;0.001). …”
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Common gene-network signature of different neurological disorders and their potential implications to neuroAIDS. by Vidya Sagar, S Pilakka-Kanthikeel, Paola C Martinez, V S R Atluri, M Nair

“…An mRNA microarray analysis in HIV-infected monocytes showed significant changes in the expression of several genes of this in silico derived common pathway which suggests the possible physiological relevance of this gene-circuit in driving neuroAIDS condition. …”
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Cysteine‐rich intestinal protein 1 enhances the progression of hepatocellular carcinoma via Ras signaling by Hong‐Yu He, Li Hu

“…To further evaluate whether CRIP1 interacts with Ras, a specific siRNA targeting Ras was selected. We found that Ras knockdown reduced the activation of Ras/AKT signaling even in HepG2 cells transfected with CRIP1. …”
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Investigation of Underlying Biological Association and Targets between Rejection of Renal Transplant and Renal Cancer by Yinwei Chen, Zhanpeng Liu, Qian Yu, Xu Sun, Shuai Wang, Qingyi Zhu, Jian Yang, Rongjiang Jiang

“…Finally, the PLAC8 was selected for further research, including its clinical and biological role. …”
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Maternal cocaine administration in mice alters DNA methylation and gene expression in hippocampal neurons of neonatal and prepubertal offspring. by Svetlana I Novikova, Fang He, Jie Bai, Nicholas J Cutrufello, Michael S Lidow, Ashiwel S Undieh

“…Endogenous expression of selected genes linked to the abnormally methylated CGIs was correspondingly decreased or increased by as much as 4-19-fold. …”
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Genetic variation and antioxidant response gene expression in the bronchial airway epithelium of smokers at risk for lung cancer. by Xuting Wang, Brian N Chorley, Gary S Pittman, Steven R Kleeberger, John Brothers, Gang Liu, Avrum Spira, Douglas A Bell

“…Prior microarray studies of smokers at high risk for lung cancer have demonstrated that heterogeneity in bronchial airway epithelial cell gene expression response to smoking can serve as an early diagnostic biomarker for lung cancer. …”
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Bioinformatics-based analysis of autophagy-related genes and prediction of potential Chinese medicines in diabetic kidney disease by Yufeng Xing, Zining Peng, Chaoyang Ye

“…Methods: Data from sequencing microarrays GSE30528, GSE30529, and GSE1009 in the Gene Expression Omnibus (GEO) were employed. …”
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Polymorphisms in the mitochondrial DNA control region and frailty in older adults. by Ann Z Moore, Mary L Biggs, Amy Matteini, Ashley O'Connor, Sarah McGuire, Brock A Beamer, M Danielle Fallin, Linda P Fried, Jeremy Walston, Aravinda Chakravarti, Dan E Arking

“…At baseline, frailty was identified as the presence of three or more of five indicators (weakness, slowness, shrinking, low physical activity, and exhaustion). mtDNA variation was assessed in a pilot study, including 315 individuals selected as extremes of the frailty phenotype, using an oligonucleotide sequencing microarray based on the Revised Cambridge Reference Sequence. …”
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