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ORIGINAL RESEARCH article
Front. Bioinform.
Sec. Network Bioinformatics
Volume 4 - 2024 |
doi: 10.3389/fbinf.2024.1442312
This article is part of the Research Topic Networks and Graphs in Biological Data: Current Methods, Opportunities and Challenges View all 4 articles
Microbe-Drug-Disease Relationships: Computational Predictions and Confirmations
Provisionally accepted- 1 Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran
- 2 Research Center for Pharmaceutical Nanotechnology, Tabriz University of Medical Sciences, Tabriz, Iran
Several computational approaches have been developed to uncover potential relationships between the microbiome, drugs, and disease. Complex and diverse microbial communities are closely related to human health, and the study of microbial communities plays an important role in the development of medicine and personalized medicine. Identifying potential relationships between microbe-disease-drug is not only useful for drug discovery and clinical treatment of diseases, but also contributes to a better understanding of the mechanisms of action of microbes. Compared with the complexity and high cost of biological experiments, computational methods can rapidly and efficiently predict potential interactions between microbes, drugs, and diseases, which can be a useful complement to experimental methods. In this article, the relationships between microbes, drugs and diseases are predicted based on the existing similarities and interactions using the Cytoscape software. Some of the potential relationships were confirmed by the available information, while the others require further clinical investigation. Due to the vital and important role of the microbiome in disease and medicine, there is a lack of information and studies in this area. In the future, the various interactions between drugs, microbes, and diseases may improve the understanding of personalized medicine, promote early diagnosis, and provide potential treatments for a wide range of diseases.
Keywords: microbe-disease associations, Drug-disease relationships, Computational models, computational prediction, Microbe-Drug-Disease Relationships
Received: 01 Jun 2024; Accepted: 26 Nov 2024.
Copyright: © 2024 Shokri Garjan, Samadi Pakchin and Ferdousi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Reza Ferdousi, Department of Health Information Technology, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran
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