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Updated: Oct 10, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
Published on: October 13, 2023
The mining and construction of a knowledge base for gene-disease association in mitochondrial diseases
Wei Wang1,2,3,4, Junying Song3, Yunhai Chuai1
1Department of Obstetrics and Gynecology, The Seventh Medical Center of Chinese PLA General Hospital, No. 5, Nanmencang Hutong, Dongsishitiao, Dongcheng District, Beijing, 100027, China.
Abstract:
Mitochondrial diseases are a group of heterogeneous genetic metabolic diseases caused by mitochondrial DNA (mtDNA) or nuclear DNA (nDNA) gene mutations. Mining the gene-disease association of mitochondrial diseases is helpful for understanding the pathogenesis of mitochondrial diseases, for carrying out early clinical diagnosis for related diseases, and for formulating better treatment strategies for mitochondrial diseases. This project researched the relationship between genes and mitochondrial diseases, combined the Malacards, Genecards, and MITOMAP disease databases to mine the knowledge on mitochondrial diseases and genes, used database integration and the sequencing method of the phenolyzer tool to integrate disease-related genes from different databases, and sorted the disease-related candidate genes. Finally, we screened 531 mitochondrial related diseases, extracted 26,723 genes directly or indirectly related to mitochondria, collected 24,602 variant sites on 1474 genes, and established a mitochondrial disease knowledge base (MitDisease) with a core of genes, diseases, and variants. This knowledge base is helpful for clinicians who want to combine the results of gene testing for diagnosis, to understand the occurrence and development of mitochondrial diseases, and to develop corresponding treatment methods.
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