Comparison of West Nile Proteome Sequences using Co-Occurrence Networks
Advisor Information
Kathryn Cooper
Location
MBSC 201
Presentation Type
Poster
Start Date
6-3-2020 10:45 AM
End Date
6-3-2020 12:00 PM
Abstract
According to the CDC, West Nile virus is the leading cause of mosquito-borne disease in the continental US, with approximately 80% of cases being asymptomatic. Creating a platform integrating publicly available big genomic and health data in order to predict, surveil, and manage viral infectious diseases such as West Nile may help mitigate the spread of such illnesses on a national scale. Especially as global warming allows mosquitoes and other exotic virus vectors to spread beyond their typical geographic locations, a database with real-time geographic visualization becomes incredibly useful. This project aims to build a specific functionality of this proposed platform by creating networks of West Nile virus strains which will provide insight into critical nucleotides that are important to the pathogenicity of each strain. Understanding these genetic causes and trends of West Nile pathogenicity will, in turn, provide knowledge into the mechanisms of lethality and/or transmissibility, and showcase evolutionary trends. In order to do this, the venture will integrate various public databases, such as the NCBI’s Virus Variation Database. This database houses thousands of genomic and proteomic sequences of West Nile virus strains, from around the world. The database is particularly useful as the virus data can be filtered by genetic characteristics, geographic region/country collected, species, or tissue isolation source, providing further specification for research.
Comparison of West Nile Proteome Sequences using Co-Occurrence Networks
MBSC 201
According to the CDC, West Nile virus is the leading cause of mosquito-borne disease in the continental US, with approximately 80% of cases being asymptomatic. Creating a platform integrating publicly available big genomic and health data in order to predict, surveil, and manage viral infectious diseases such as West Nile may help mitigate the spread of such illnesses on a national scale. Especially as global warming allows mosquitoes and other exotic virus vectors to spread beyond their typical geographic locations, a database with real-time geographic visualization becomes incredibly useful. This project aims to build a specific functionality of this proposed platform by creating networks of West Nile virus strains which will provide insight into critical nucleotides that are important to the pathogenicity of each strain. Understanding these genetic causes and trends of West Nile pathogenicity will, in turn, provide knowledge into the mechanisms of lethality and/or transmissibility, and showcase evolutionary trends. In order to do this, the venture will integrate various public databases, such as the NCBI’s Virus Variation Database. This database houses thousands of genomic and proteomic sequences of West Nile virus strains, from around the world. The database is particularly useful as the virus data can be filtered by genetic characteristics, geographic region/country collected, species, or tissue isolation source, providing further specification for research.