Bioinformatics, Experimental and Computational Biology for Personalized Medicine in Chronic Diseases 2021
1Shanghai University, Shanghai, China
2Deakin University, Melbourne, Australia
3Guangxi Medical University, Nanning, China
4Tongji University School of Medicine, Shanghai, China
5Imperial College London, London, UK
Bioinformatics, Experimental and Computational Biology for Personalized Medicine in Chronic Diseases 2021
Description
Chronic diseases such as diabetes, cancer, and dry eye disease can become epidemics which eventually threaten human health. The primary reason for this is our inability to detect, diagnose, and treat these diseases. The number of patients with these chronic diseases is increasing rapidly worldwide, and 75% and 85% of the deaths are caused by these diseases in the USA and China, respectively. This accounts for up to 70% of the total disease burden of these countries. In the future, chronic diseases including cardiovascular and cerebrovascular diseases, malignant tumours, and diabetes are very likely to rise.
In the past two decades, with the rapid development of such techniques as high-throughput sequencing, gene editing, and immunotherapy, as well as the discovery of related key genes or pathways in chronic diseases, increasingly in-depth studies of chronic diseases biology have been spurred at the genetic and genomic levels. This has led to better targeted and personalized healthcare solutions for patients. However, this poses a huge challenge for the integration, utilization, and analysis of all the accompanying components.
In this Special Issue, we invite authors to contribute original research articles or reviews for the current problems in these areas.
Potential topics include but are not limited to the following:
- Discovery of new targets or biomarkers, new diagnostic therapeutic agents, and active targeting agents
- Protein function and structure analysis and prediction
- Modification site analysis and identification in protein, DNA, and RNA
- Clinical data analysis using artificial intelligent techniques
- Drug target discovery and targeted drug design
- Personalized therapy based on artificial intelligent techniques
- NMR spectroscopy, X-ray cryptography, 3D structures of target proteins/RNA/DNA
- Disease prediction based on Artificial Intelligence