Integrated analysis of hub genes and intrinsically disordered regions in triple-negative breast cancer by Azhar Iqbal, Faisal Ali, Sulaiman Ali Alharbi, Muhammad Sajid, Saleh Alfarraj, Momina Hussain, Tehmina Siddique, Rakhshanda Mustaq, Fakhra Shafique, Muhammad Sarfaraz Iqbal

“…Despite several attempts, the molecular pathways of TNBC remain unknown, posing a significant clinical barrier in the search for viable targets. Two microarray datasets were used to identify possible targets for TNBC, GSE38959 and GSE45827, retrieved from the Gene Expression Omnibus (GEO) database. …”
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Early diagnosis of acute myocardial infarction via hub genes identified by integrated weighted gene co-expression network analysis by Kun Huang, Feng Wen, Jingyi Li, Wenhao Niu, Hui Chen, Shilei Wan, Fupeng Yang, Yihong Chen, Chun Liang

“…Diagnostic biomarkers were selected and identified using three machine learning algorithms. …”
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MicroRNA let-7f protects against H2O2-induced oxidative damage in neuroblastoma cells by targeting AKT-2 by Kuo Li, Zhan-Qiang Wang, Jun-Ling Zhang, Pei-Yuan Lv

“…Material and methods miRNA microarray analysis was performed to detect the miRNAs’ differential expression in AD patients and normal elderly volunteers. …”
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Endoplasmic reticulum stress-related CLIP4 plays a procarcinogenic role in hepatocellular carcinoma: an integrated analysis by Anqi Wang, Sitong Yan, Weijia Jiang, Xiang Chen, Yuhan Huang, Xiangyu Zu, Xiao Du, Lulu Fan, Jiatao Liu, Guoping Sun

“…Methods TCGA public database and a tissue microarray were used to investigate the molecular characteristics of CLIP4 and its association with disease. …”
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Identification and validation of hub genes associated with biotic and abiotic stresses by modular gene co-expression analysis in Oryza sativa L. by Izreen Izzati Razalli, Muhammad-Redha Abdullah-Zawawi, Rabiatul Adawiah Zainal Abidin, Sarahani Harun, Muhamad Hafiz Che Othman, Ismanizan Ismail, Zamri Zainal

“…A total of 11, 12, 46, and 14 modules containing 85, 106, 253, and 143 hub genes were detected in drought, salinity, tungro virus, and blast. …”
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Expression and clinical significance of FGL1 and YAP1 in colorectal cancer by LIU Yuanming*，CUI Guangjie，CHEN Jiaqi，LU Yang，GAO Chao

“…<b>Methods</b> Tissue microarray technique was used to detect FGL1 and YAP1 expression in 101 colorectal cancer tissues and 79 adjacent tissues from June 2007 to April 2008. …”
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Penaeus vannamei Genetic Evaluation for Growth and Survival Traits During White Spot Syndrome Virus Infection Based on 55K SNP Chip by Yijing HE, Mianyu LIU, Sheng LUAN, Jie KONG, Xupeng LI, Baoxiang CAO, Kun LUO, Jian TAN, Jiawang CAO, Ping DAI, Guangfeng QIANG, Zhaoxin WANG, Juan SUI, Xianhong MENG

“…Based on the survival time of individual resistance to WSSV within the family line, 590 individuals were uniformly selected and typed using 55K SNP liquid-phase microarrays to obtain genotypic data for certain individuals. …”
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KRT6A, KRT6B, PKP1, and PKP3 as key hub genes in esophageal cancer: A combined bioinformatics and experimental study by Shayan Marhamati, Morvarid Hamrahjoo, Zeinab Seyedkhan, Mahdi Bahmani, Nasrin Ziamajidi, Iraj Khodadadi, Mohadese Pouryani, Roghayeh Abbasalipourkabir

“…In this study, we downloaded the microarray datasets GSE157808 and GSE92396 from the Gene Expression Omnibus (GEO). …”
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New Frontiers for the Early Diagnosis of Cancer: Screening miRNAs Through the Lateral Flow Assay Method by Afsaneh Emamiamin, Seyedeh Rojin Shariati Pour, Thea Serra, Donato Calabria, Marta Varone, Fabio Di Nardo, Massimo Guardigli, Laura Anfossi, Claudio Baggiani, Martina Zangheri, Mara Mirasoli

“…This review focuses on LFA-based methods for detecting and quantifying miRNAs associated with the diagnosis of various cancers, with particular emphasis on sensitivity enhancements achieved through the application of different labels and detection systems. …”
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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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Differentiating Branch Duct and Mixed IPMN in Endoscopically Collected Pancreatic Cyst Fluid via Cytokine Analysis by Linda S. Lee, Andrew M. Bellizzi, Peter A. Banks, Nisha I. Sainani, Vivek Kadiyala, Shadeah Suleiman, Darwin L. Conwell, Joao A. Paulo

“…Eighty-six of 89 IMPs were detected in at least one of the 10 samples. Fourteen IMPs were detected only in mixed IPMN, while none were only in BD-IPMN. …”
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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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Genome-wide analysis in the search for candidate genes associated with meat productivity traits in meat-and-dairy goats by M. I. Selionova, A.-M. M. Aibazov, A. A. Sermyagin, A. A. Belous, N. A. Zinovieva

“…GWAS analysis using Goat 50K BeadChip high-density DNA microarray determined a genome-wide level of significance for six SNPs located on chromosomes 5, 6, 10 and 16 associated with the live weight of young animals (4 and 8 months old). …”
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Spatial transcriptomic characteristics of gastric cancer in young and the expression and role of TMEM176B in gastric cancer cells by Zhenhua Jiang, Yongfeng Wang, Chi Zhang, Shuangyin Han

“…Methods The surgical specimens of six patients with GCY were included to construct a tissue microarray containing the tumor core region (TCR), cancer-adjacent tissue (CAT), and normal gastric tissue (NGT). …”
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Screening of endoplasmic reticulum stress characteristic genes and immune infiltration manifestations in chronic obstructive pulmonary disease by ZHANG Shuang, LUO Chenyang, HE Zhiyi

“…At the same time, co-expressed mRNA and miRNA were selected to construct the mRNA-miRNA interaction network. …”
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Comprehensive bioinformatics analysis identifies hub genes associated with immune cell infiltration in early-onset schizophrenia by Shasha Wu, Tailian Xue, Yilin Li, Weikang Chen, Yan Ren

“…Methods In this study, we recruited 26 EOS patients and 27 healthy controls (HCs), and microarray data were collected. Crossover genes were identified using weighted gene co-expression network analysis (WGCNA) and differential expression genes (DEGs) analysis. …”
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Identification of CD36 as a contributor in inflammatory response of rheumatoid arthritis and screening of feasible bioactive drugs targeting it by Dan Xuan, Xiaowan Wang, Dandan Feng, Li Wang, Yonghui Xia

“…Methods RA-related microarray datasets (GSE77298 and GSE206848) and inflammatory genes (IRGs) were downloaded from Gene Expression Omnibus database and GeneCards database, respectively. …”
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MiR-223-3p regulates erythropoiesis by targeting TGFBR3/Smad signaling pathway in hemoglobin H-Constant Spring disease by Lan Lan, Xinyu Wang, Simeng Zhang, Dan Zeng, Limin Mo, Qiao Feng, Jun Li, Chunjiang Zhu

“…The present study analyzed miRNAs differential expression profile between patients with HbH-CS disease and healthy subjects by Arraystar Human small RNA Microarray.Methods The differential expression profiles of miRNAs between HbH-CS patients and healthy individuals were analyzed using Arraystar human small RNA microarrays. …”
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Patterns of Human Respiratory Viruses and Lack of MERS-Coronavirus in Patients with Acute Upper Respiratory Tract Infections in Southwestern Province of Saudi Arabia by Ahmed A. Abdulhaq, Vinod Kumar Basode, Anwar M. Hashem, Ahmed S. Alshrari, Nassrin A. Badroon, Ahmed M. Hassan, Tagreed L. Alsubhi, Yahia Solan, Saleh Ejeeli, Esam I. Azhar

“…MERS-CoV was not detected in any of the samples. Human rhinovirus (hRV) was the most detected pathogen (40.9%) followed by non-MERS-CoV human coronaviruses (19.3%), influenza (Flu) viruses (15.9%), and human respiratory syncytial virus (hRSV) (13.6%). …”
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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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