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Identification of Anoikis-Related Genes in Chronic Kidney Disease Based on Bioinformatics Analysis Combined with Experimental Validation.
J Inflamm Res
January 2025
Department of Pharmacology, School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, People's Republic of China.
Background: Chronic kidney disease (CKD) is a progressive condition that arises from diverse etiological factors, resulting in structural alterations and functional impairment of the kidneys. We aimed to establish the Anoikis-related gene signature in CKD by bioinformatics analysis.
Methods: We retrieved 3 datasets from the Gene Expression Omnibus (GEO) database to obtain differentially expressed genes (DEGs), followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, Gene Set Enrichment Analysis (GSEA) and Gene Set Variation Analysis (GSVA) of them, which were intersected with Anoikis-related genes (ARGs) to derive Anoikis-related differentially expressed genes (ARDEGs).
MBCdeg4: A modified clustering-based method for identifying differentially expressed genes from RNA-seq data.
MethodsX
June 2025
Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi 1-1-1, Bunkyo-ku, Tokyo 113-8657, Japan.
RNA-seq is a commonly employed methodology for the measurement of transcriptomes, particularly for the identification of differentially expressed genes (DEGs) between different conditions or groups. In a previous report, we described a clustering-based method for identifying DEGs, designated MBCdeg1 and MBCdeg2. and a modified version, MBCdeg3.
View Article and Find Full Text PDFIdentification of Ferroptosis-related Genes for Diabetic Nephropathy by Bioinformatics and Experimental Validation.
Curr Pharm Des
January 2025
Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing 210029, Jiangsu Province, China.
Objective: The present study delves into the exploration of diagnostic biomarkers linked with ferroptosis in the context of diabetic nephropathy, unraveling their underlying molecular mechanisms.
Methods: In this study, we retrieved datasets GSE96804 and GSE30529 as the training cohort, followed by screening for Differentially Expressed Genes (DEGs). By intersecting these DEGs with known ferroptosisrelated genes, we obtained the differentially expressed genes related to ferroptosis (DEFGs).
Identification of novel cytoskeleton protein involved in spermatogenic cells and sertoli cells of non-obstructive azoospermia based on microarray and bioinformatics analysis.
BMC Med Genomics
January 2025
Department of Surgery, Faculty of General of Medicine, Koya University, Koya, Kurdistan Region - F.R., KOY45, Iraq.
Background: During mammalian spermatogenesis, the cytoskeleton system plays a significant role in morphological changes. Male infertility such as non-obstructive azoospermia (NOA) might be explained by studies of the cytoskeletal system during spermatogenesis.
Methods: The cytoskeleton, scaffold, and actin-binding genes were analyzed by microarray and bioinformatics (771 spermatogenic cellsgenes and 774 Sertoli cell genes).
Analysis and identification of potential biomarkers for dysfunctional uterine bleeding.
J Reprod Immunol
January 2025
Department of Chinese Medicine Rehabilitation, The First Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, Guiyang 50001, China. Electronic address:
Clinical evidence increasingly suggests that traditional treatments for dysfunctional uterine bleeding (DUB) have limited success. In this study, blood samples from 10 DUB patients and 10 healthy controls were collected for transcriptome sequencing. Then, the differentially expressed genes (DEGs) were screened and crossed with the DUB-related module genes to obtain the target genes.
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