New Dimensions of Computational Biology and Its Applications in Chronic Diseases
A special issue of Medicina (ISSN 1648-9144). This special issue belongs to the section "Translational Medicine".
Deadline for manuscript submissions: closed (31 March 2022) | Viewed by 281
Special Issue Editor
Special Issue Information
Dear Colleagues,
High-throughput sequencing has become a mainstream sequencing technology that enables researchers to detect symmetry-breaking events in the genomes and transcriptomes of human diseases. Empowered by quantitative sciences and computational advances, we are now able to identify signatures of pathogenic processes from mega-sized datasets and better understand the role of symmetry disruption in chronic diseases at different molecular levels. With the help of computational biology, genetic data can be used to improve the current clinical practices of prevention, diagnosis, prognosis and targeted therapy of chronic disease.
This Special Issue aims to highlight the role of computational biology in chronic diseases as an advanced tool for chronic disease management, with special emphasis given to clinical implications. Potential topics include but are not limited to:
- Big Data analysis in computational biologyin chronic diseases;
- Machine learning and data mining in bioinformatics and computational biologyin chronic diseases;
- Machine learning and deep learning in chronic diseases;
- AI for diagnostics in chronic diseases;
- Imaging data analysis (imaging genomics);
- Analysis of patient treatment information and outcome prediction with big data structure.
Prof. Dr. Qiyuan Li
Guest Editor
Manuscript Submission Information
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Keywords
- Chronic Disease
- High throughput sequencing
- computational biology
- Symmetry
- clinical practice
