Article

Integrative bioinformatics analyses of mitochondrial dysfunction-related genes in human non-obstructive azoospermia

2025-07-25

Abstract excerpt

<title>Abstract</title> <p> Non-obstructive azoospermia (NOA) is the severest form of male infertility. This study aimed to identify core genes associated with mitochondrial dysfunction and regulatory networks in NOA, providing potential diagnostic biomarkers and therapeutic targets for NOA. Three microarray-based transcriptome datasets (GSE108886, GSE145467, GSE9210) of testis tissue were analyzed. Mitochondria...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: bba48a20-e432-5d63-bb3a-741ab98190df
DOI: 10.21203/rs.3.rs-7035452/v1

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Integrative bioinformatics analyses of mitochondrial dysfunction-related genes in human non-obstructive azoospermiaDOI 10.21203/rs.3.rs-7035452/v1Read

Integrative bioinformatics approaches for identifying potential biomarkers and pathways involved in non-obstructive azoospermiaSemantic proximity Read

Screening and identification of critical Genes and Pathways Associated with Oxidative Stress in non-obstructive azoospermia patients: an integrative bioinformatics studySemantic proximity Read

Identification and Potential Value of Candidate Genes in Patients With Non-obstructive AzoospermiaSemantic proximity Read

Machine learning and integrative analysis identify the common pathogenesis of azoospermia complicated with COVID-19Semantic proximity Read

Identification of ferroptotic genes and phenotypes in idiopathic nonobstructive azoospermia.Semantic proximity Read

Whole Exome Sequencing and In Silico Analysis of Human Sertoli in Patients with Non-Obstructive AzoospermiaSemantic proximity Read

Omics and Male Infertility: Highlighting the Application of Transcriptomic DataSemantic proximity Read

Whole exome sequencing identifies genes associated with non-obstructive azoospermiaSemantic proximity Read

Using publicly available transcriptomic data to identify mechanistic and diagnostic biomarkers in azoospermia and overall male infertilitySemantic proximity Read

Multiomics identification of programmed cell death-related characteristics for nonobstructive azoospermia based on a 675-combination machine learning computational framework.Semantic proximity Read

Weighted Correlation Gene Network Analysis Reveals New Potential Mechanisms and Biomarkers in Non-obstructive AzoospermiaSemantic proximity Read

Identifying potential biomarkers for non-obstructive azoospermia using WGCNA and machine learning algorithmsSemantic proximity Read