Please use this identifier to cite or link to this item: http://repository.iiitd.edu.in/xmlui/handle/123456789/2087
Title: Genomic embedding-based modeling and classification of dengue virus serotypes
Authors: Rao, Decee
Mangla, Abhinav
Sethi, Tavpritesh (Advisor)
Keywords: Dengue virus
Machine Learning
Intra-host Variation
Public Health Genomics
Issue Date: 18-Jul-2025
Publisher: IIIT-Delhi
Abstract: The rising burden of dengue across tropical regions necessitates a deeper understanding of its evolutionary dynamics, especially under the influence of climate variability and host factors. This project aims to investigate intra-host genetic variations in the dengue virus (DENV) and explore their correlation with clinical severity and outbreak potential. Leveraging whole genome sequences from dengue patients, we analyze serotype-specific mutation patterns, lineage fitness, and dominant clade dynamics. Additionally, we assess geo-temporal trends and quantify the impact of climatic factors such as temperature, humidity, and rainfall on viral evolution. By integrating genomic data with environmental variables and clinical profiles, the study lays the foundation for predictive modeling of dengue severity and spread. This interdisciplinary ap proach not only enhances our understanding of dengue pathogenesis but also supports future outbreak forecasting and intervention strategies.
URI: http://repository.iiitd.edu.in/xmlui/handle/123456789/2087
Appears in Collections:Year-2025

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