Yutao Wu, Yi Zhou, Wenjing Shi, Siyu Zhou, Min Jiang, Ke Shen, Xingyun Liu, Xiaoyu Li, Jiao Wang, Chi Zhang, Bairong Shen, Weidong Tian
{"title":"ORMCKB: A Knowledge Database for Personalized Medicine in Deciphering the Oral Microbiome-Disease Axis.","authors":"Yutao Wu, Yi Zhou, Wenjing Shi, Siyu Zhou, Min Jiang, Ke Shen, Xingyun Liu, Xiaoyu Li, Jiao Wang, Chi Zhang, Bairong Shen, Weidong Tian","doi":"10.1007/s12539-025-00769-5","DOIUrl":null,"url":null,"abstract":"<p><p>The oral microbiome plays a crucial role in the development and progression of diseases. The complex interactions between the oral microbiome and diseases are challenging for clinicians in clinical decision-making and scientific research. To address this gap, we developed an oral microbiome knowledge database (ORMCKB), to provide evidence for personalized medicine and scientific research in the oral microbiome-disease axis. The current version of ORMCKB contains 11,554 data entries, encompassing 6941 oral microbe taxonomies, 234 diseases, 220 interventions, and 175 bacteriostats extracted from 818 publications. Compared to ChatGPT-4o, ORMCKB demonstrates superior performance in matching questions with responses (10 vs. 9.6), presenting research article details (10 vs. 5.80), and recommended scientific article authenticity ratio (100% vs. 33.63%). The system usability scale (SUS) and the net promoter score (NPS) were 86.07 and 85.71, respectively. As the first knowledge database focused on the oral microbiome-disease axis, ORMCKB provides a comprehensive, accurate, and user-friendly online resource for identifying key microbial players and their associations with oral diseases in personalized medicine. ORMCKB is set to sustain its prominence in cutting-edge research on the oral microbiome-disease axis, paving the way for future artificial intelligence applications in both scientific research and clinical practice. ORMCKB is publicly available at: http://sysbio.org.cn/ormckb.</p>","PeriodicalId":13670,"journal":{"name":"Interdisciplinary Sciences: Computational Life Sciences","volume":" ","pages":""},"PeriodicalIF":3.9000,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Interdisciplinary Sciences: Computational Life Sciences","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1007/s12539-025-00769-5","RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
The oral microbiome plays a crucial role in the development and progression of diseases. The complex interactions between the oral microbiome and diseases are challenging for clinicians in clinical decision-making and scientific research. To address this gap, we developed an oral microbiome knowledge database (ORMCKB), to provide evidence for personalized medicine and scientific research in the oral microbiome-disease axis. The current version of ORMCKB contains 11,554 data entries, encompassing 6941 oral microbe taxonomies, 234 diseases, 220 interventions, and 175 bacteriostats extracted from 818 publications. Compared to ChatGPT-4o, ORMCKB demonstrates superior performance in matching questions with responses (10 vs. 9.6), presenting research article details (10 vs. 5.80), and recommended scientific article authenticity ratio (100% vs. 33.63%). The system usability scale (SUS) and the net promoter score (NPS) were 86.07 and 85.71, respectively. As the first knowledge database focused on the oral microbiome-disease axis, ORMCKB provides a comprehensive, accurate, and user-friendly online resource for identifying key microbial players and their associations with oral diseases in personalized medicine. ORMCKB is set to sustain its prominence in cutting-edge research on the oral microbiome-disease axis, paving the way for future artificial intelligence applications in both scientific research and clinical practice. ORMCKB is publicly available at: http://sysbio.org.cn/ormckb.
期刊介绍:
Interdisciplinary Sciences--Computational Life Sciences aims to cover the most recent and outstanding developments in interdisciplinary areas of sciences, especially focusing on computational life sciences, an area that is enjoying rapid development at the forefront of scientific research and technology.
The journal publishes original papers of significant general interest covering recent research and developments. Articles will be published rapidly by taking full advantage of internet technology for online submission and peer-reviewing of manuscripts, and then by publishing OnlineFirstTM through SpringerLink even before the issue is built or sent to the printer.
The editorial board consists of many leading scientists with international reputation, among others, Luc Montagnier (UNESCO, France), Dennis Salahub (University of Calgary, Canada), Weitao Yang (Duke University, USA). Prof. Dongqing Wei at the Shanghai Jiatong University is appointed as the editor-in-chief; he made important contributions in bioinformatics and computational physics and is best known for his ground-breaking works on the theory of ferroelectric liquids. With the help from a team of associate editors and the editorial board, an international journal with sound reputation shall be created.