Comprehensive analysis of cuproptosis-related genes in immune infiltration and development of a novel diagnostic model for acute kidney injury by Yajing Li, Yingxue Ding

“…Our study aimed to investigate the involvement of cuproptosis-related genes (CRGs) in AKI.Methods Identification of CRGs was conducted using differential expression analysis, and subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using human sequencing profiles. …”
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Identification of Signal Pathways and Hub Genes of Pulmonary Arterial Hypertension by Bioinformatic Analysis by Rui-Qi Wei, Wen-Mei Zhang, Zhe Liang, Chunmei Piao, Guangfa Zhu

“…All the raw data were processed by R, and differentially expressed genes (DEGs) were screened out by the “limma” package. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed and visualized by R and Cytoscape software. …”
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Orígenes de la Psicología Discursiva y su desarrollo hacia una psicología cultural postmoderna by Hugo Ignacio Campos Winter

“…The psychological concepts and in particular the concept of identity seen from discursive psychology experienced a shift not only in its methodological approach but also in its ontology, acquiring a discursive essence. Finally, an assembly of discursive psychology and postmodern anthropology aims to generate a new concept of cultural identity and to outline the possible development of discursive psychology into a new postmodern cultural psychology. …”
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Bioinformatics Analysis of Exercise-Related Biomarkers in Diabetes by Xiaoju Bao, Jingyue Qiu, Qin Xuan, Xinming Ye

“…Then, the enrichment analysis of DEGs in Gene Ontology (GO) function was analyzed by Metascape, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of DEGs was also analyzed by gene set enrichment analysis (GSEA). …”
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Genome-Wide Association Studies Associated with Backfat Thickness in Landrace and Yorkshire Pigs by Young-Sup Lee, Donghyun Shin

“…We conducted a GWAS and surveyed the gene ontology (GO) terms associated with the backfat thickness (BF) trait of these pigs. …”
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Identification of Differentially Expressed lncRNAs in a CpG ODN-Activated Macrophage by Ying Zheng, Xi Luo, Zailong Qin, Zhiguang Zhou

“…The results revealed that expression levels of 734 lncRNAs and 734 mRNAs were altered at all time points. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analyses were performed to predict the functions of dysregulated genes. …”
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RNA Sequencing Reveals the Differentially Expressed circRNAs between Stable and Unstable Carotid Atherosclerotic Plaques by Xueguang Lin, Ying Deng, Lujuan Ye, Bo Chen, Jindong Tong, Weijun Shi, Bo Wang, Bo Yu, Jingdong Tang

“…Functional evaluation of the DE circRNAs was conducted via Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. …”
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Pathological and Molecular Characterization of Grass Carp Co-Infected with Two <i>Aeromonas</i> Species by Wenyao Lv, Zhijie Zhou, Lingli Xie, Xinyue Wang, Yifei Zhou, Lang Gui, Xiaoyan Xu, Yubang Shen, Jiale Li, Junqiang Qiu

“…Comparative transcriptomic analysis of hepatic tissues between co-infected and control specimens identified 868 and 411 differentially expressed genes (DEGs) at 1 and 5 dpi, respectively. Gene ontology and KEGG pathway analyses revealed significant enrichment of immune-related genes primarily associated with Toll-like receptor signaling and TNF signaling cascades. …”
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The storage quality and transcriptome analysis of fresh-cut taro by L-ascorbic acid combined with ultrasonic treatment by Lin Chen, Bingzhi Chen, Lulu Chu, Lili Chen, Luyu Xie, Youjin Deng, Yuji Jiang

“…Transcriptome analysis revealed that differentially expressed genes (DEGs) between the AS and CK groups were annotated and categorized into 50 and 20 functional groups based on the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, respectively. …”
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Detection of HIV-1 and Human Proteins in Urinary Extracellular Vesicles from HIV+ Patients by Samuel I. Anyanwu, Akins Doherty, Michael D. Powell, Chamberlain Obialo, Ming B. Huang, Alexander Quarshie, Claudette Mitchell, Khalid Bashir, Gale W. Newman

“…Western blots confirmed the presence of HIV proteins. Gene ontology (GO) analysis was performed using FunRich and HIV Human Interaction database (HHID). …”
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Investigation of metabolic features of glioblastoma tissue and the peritumoral environment using targeted metabolomics screening by LC-MS/MS and gene network analysis by N. V. Basov, A. V. Adamovskaya, A. D. Rogachev, E. V. Gaisler, P. S. Demenkov, T. V. Ivanisenko, A. S. Venzel, S. V. Mishinov, V. V. Stupak, S. V. Cheresiz, O. S. Oleshko, E. A. Butikova, A. E. Osechkova, Yu. S. Sotnikova, Y. V. Patrushev, A. S. Pozdnyakov, I. N. Lavrik, V. A. Ivanisenko, A. G. Pokrovsky

“…Analysis of the overrepresentation of Gene Ontology biological processes revealed the statistical significance of 184 processes, including apoptosis, the NF-kB signaling pathway, proliferation, migration, angiogenesis, and py­roptosis, many of which play an important role in oncogenesis. …”
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New insights into the mechanism of triphenyl phosphate and its metabolite diphenyl phosphate in diabetic kidney disease by Ting Fang, Qiaoyan Liu, Xinxin Huangfu, Hongkai Zhu, Hongwen Sun, Liming Chen

“…Additionally, the study explored the targets of action for TPHP and DPHP using network toxicity analysis, conducted protein interaction analysis, and explored the functional aspects of action through Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis. …”
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Differential Gene Expression Analysis in a Lumbar Spinal Stenosis Rat Model via RNA Sequencing: Identification of Key Molecular Pathways and Therapeutic Insights by Jin Young Hong, Wan-Jin Jeon, Hyunseong Kim, Changhwan Yeo, Hyun Kim, Yoon Jae Lee, In-Hyuk Ha

“…Functional enrichment analysis revealed that these DEGs included those involved in key biological processes, including synaptic plasticity, extracellular matrix organization, and hormonal regulation. Gene ontology analysis highlighted critical molecular functions such as mRNA binding and integrin binding, as well as cellular components such as contractile fibers and the extracellular matrix, which were significantly affected by LSS. …”
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Novel histone deacetylase-5 inhibitor T2943 exerts an anti-depressive effect in mice by enhancing GRID1 expression by Juan Du, Ruyun Liu, Lin Ma, Yue Liu, Wei Wei, Ning Liu, Qiuhua Cao, Jianqiang Yu

“…We used cleavage under targets and tagmentation (CUT&Tag), gene set enrichment analysis, and behavioral tests after GRID1 (glutamate receptor delta-1 subunit) knockdown. Gene ontology and pathway enrichment analysis via CUT&Tag suggested the following mechanism for the antidepressant action of T2943: T2943 inhibits HDAC5 activity to promote H3K14 acetylation. …”
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Early transcriptomic changes at the skin interface during Powassan virus transmission by Ixodes scapularis ticks by Dakota N. Paine, Dakota N. Paine, Meghan Hermance, Saravanan Thangamani, Saravanan Thangamani, Saravanan Thangamani

“…Differentially expressed genes were analyzed for pathway enrichment using gene ontology and pathway enrichment analyses.ResultsOur findings reveal that tick feeding alone significantly impacts the skin transcriptome within the first 1 to 3 h of tick attachment. …”
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Plasmatic Membrane Expression of Adhesion Molecules in Human Cardiac Progenitor/Stem Cells Might Explain Their Superior Cell Engraftment after Cell Transplantation by Imelda Ontoria-Oviedo, Itziar Palacios, Joaquín Panadero, Belén Sánchez, Francisco García-García, Adolfo López-Cerdán, Akaitz Dorronsoro, Delia Castellano, Luis Rodríguez-Borlado, Antonio Bernad, Pilar Sepúlveda

“…Analysis of the receptome of CPCs and BM-MSCs showed that gene ontology biological processes and KEGG pathways associated with adhesion mechanisms were upregulated in CPCs compared with BM-MSCs. …”
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CD14loCD301b+ macrophages gathering as a proangiogenic marker in adipose tissues by Yibing Lv, Yidan Zheng, Shanshan Su, Junyi Xiao, Jie Yang, Lingyun Xiong, Yanyan Guo, Xiaoqi Zhou, Nengqiang Guo, Ping Lei

“…To investigate the underlying mechanisms, adipose tissues (ATs) from Cd14−/− and WT mice were subjected to deep RNA sequencing. Gene Ontology enrichment analysis revealed a significant enhancement of angiogenesis-related function in the Cd14−/− epididymal adipose tissues compared to WT counterpart, which was accompanied by an upregulation of Cd301b. …”
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The Identification of Key Genes and Pathways in Glioma by Bioinformatics Analysis by Mingfa Liu, Zhennan Xu, Zepeng Du, Bingli Wu, Tao Jin, Ke Xu, Liyan Xu, Enmin Li, Haixiong Xu

“…The glioma gene expression profile GSE4290 was analyzed for differentially expressed genes (DEGs). Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were applied for the enriched pathways. …”
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Molecular Networks Involved in the Immune Control of BK Polyomavirus by Eva Girmanova, Irena Brabcova, Jiri Klema, Petra Hribova, Mariana Wohlfartova, Jelena Skibova, Ondrej Viklicky

“…., CD40/CD40L; P<0.05). Gene ontology analysis revealed several biological networks associated with BKV immune control in comparison to the control group. …”
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Better understanding the phenotypic effects of drugs through shared targets in genetic disease networks by Elena Díaz-Santiago, Aurelio A. Moya-García, Jesús Pérez-García, Raquel Yahyaoui, Raquel Yahyaoui, Christine Orengo, Florencio Pazos, James R. Perkins, James R. Perkins, James R. Perkins, Juan A. G. Ranea, Juan A. G. Ranea, Juan A. G. Ranea, Juan A. G. Ranea

“…Gaining traction in this field is the use of disease data linking genes with pathological phenotypes and combining this with drugtarget interaction data.MethodsWe introduce methodology to associate drugs with effects, both intended and adverse, using a tripartite network approach that combines drug-target and target-phenotype data, in which targets can be represented as proteins and protein domains.ResultsWe were able to detect associations for over 140,000 ChEMBL drugs and 3,800 phenotypes, represented as Human Phenotype Ontology (HPO) terms. The overlap of these results with the SIDER databases of known drug side effects was up to 10 times higher than random, depending on the target type, disease database and score threshold used. …”
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