{"title":"DisGeNet:疾病和各种相关基因之间以疾病为中心的相互作用数据库。","authors":"Yaxuan Hu, Xingli Guo, Yao Yun, Liang Lu, Xiaotai Huang, Songwei Jia","doi":"10.1093/database/baae122","DOIUrl":null,"url":null,"abstract":"<p><p>The pathogenesis of complex diseases is intricately linked to various genes and network medicine has enhanced understanding of diseases. However, most network-based approaches ignore interactions mediated by noncoding RNAs (ncRNAs) and most databases only focus on the association between genes and diseases. Based on the mentioned questions, we have developed DisGeNet, a database focuses not only on the disease-associated genes but also on the interactions among genes. Here, the associations between diseases and various genes, as well as the interactions among these genes are integrated into a disease-centric network. As a result, there are a total of 502 688 interactions/associations involving 6697 diseases, 5780 lncRNAs (long noncoding RNAs), 16 135 protein-coding genes, and 2610 microRNAs stored in DisGeNet. These interactions/associations can be categorized as protein-protein, lncRNA-disease, microRNA-gene, microRNA-disease, gene-disease, and microRNA-lncRNA. Furthermore, as users input name/ID of diseases/genes for search, the interactions/associations about the search content can be browsed as a list or viewed in a local network-view. Database URL: https://disgenet.cn/.</p>","PeriodicalId":10923,"journal":{"name":"Database: The Journal of Biological Databases and Curation","volume":"2025 ","pages":""},"PeriodicalIF":3.4000,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11724190/pdf/","citationCount":"0","resultStr":"{\"title\":\"DisGeNet: a disease-centric interaction database among diseases and various associated genes.\",\"authors\":\"Yaxuan Hu, Xingli Guo, Yao Yun, Liang Lu, Xiaotai Huang, Songwei Jia\",\"doi\":\"10.1093/database/baae122\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The pathogenesis of complex diseases is intricately linked to various genes and network medicine has enhanced understanding of diseases. However, most network-based approaches ignore interactions mediated by noncoding RNAs (ncRNAs) and most databases only focus on the association between genes and diseases. Based on the mentioned questions, we have developed DisGeNet, a database focuses not only on the disease-associated genes but also on the interactions among genes. Here, the associations between diseases and various genes, as well as the interactions among these genes are integrated into a disease-centric network. As a result, there are a total of 502 688 interactions/associations involving 6697 diseases, 5780 lncRNAs (long noncoding RNAs), 16 135 protein-coding genes, and 2610 microRNAs stored in DisGeNet. These interactions/associations can be categorized as protein-protein, lncRNA-disease, microRNA-gene, microRNA-disease, gene-disease, and microRNA-lncRNA. Furthermore, as users input name/ID of diseases/genes for search, the interactions/associations about the search content can be browsed as a list or viewed in a local network-view. Database URL: https://disgenet.cn/.</p>\",\"PeriodicalId\":10923,\"journal\":{\"name\":\"Database: The Journal of Biological Databases and Curation\",\"volume\":\"2025 \",\"pages\":\"\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-01-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11724190/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Database: The Journal of Biological Databases and Curation\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1093/database/baae122\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Database: The Journal of Biological Databases and Curation","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1093/database/baae122","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
DisGeNet: a disease-centric interaction database among diseases and various associated genes.
The pathogenesis of complex diseases is intricately linked to various genes and network medicine has enhanced understanding of diseases. However, most network-based approaches ignore interactions mediated by noncoding RNAs (ncRNAs) and most databases only focus on the association between genes and diseases. Based on the mentioned questions, we have developed DisGeNet, a database focuses not only on the disease-associated genes but also on the interactions among genes. Here, the associations between diseases and various genes, as well as the interactions among these genes are integrated into a disease-centric network. As a result, there are a total of 502 688 interactions/associations involving 6697 diseases, 5780 lncRNAs (long noncoding RNAs), 16 135 protein-coding genes, and 2610 microRNAs stored in DisGeNet. These interactions/associations can be categorized as protein-protein, lncRNA-disease, microRNA-gene, microRNA-disease, gene-disease, and microRNA-lncRNA. Furthermore, as users input name/ID of diseases/genes for search, the interactions/associations about the search content can be browsed as a list or viewed in a local network-view. Database URL: https://disgenet.cn/.
期刊介绍:
Huge volumes of primary data are archived in numerous open-access databases, and with new generation technologies becoming more common in laboratories, large datasets will become even more prevalent. The archiving, curation, analysis and interpretation of all of these data are a challenge. Database development and biocuration are at the forefront of the endeavor to make sense of this mounting deluge of data.
Database: The Journal of Biological Databases and Curation provides an open access platform for the presentation of novel ideas in database research and biocuration, and aims to help strengthen the bridge between database developers, curators, and users.