Visual analytics of coronaviruses data

• Main Author: Tan, Xieng Yiong
• Other Authors: Sourav S Bhowmick
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2021
• Subjects: Engineering::Computer science and engineering::Information systems::Information interfaces and presentation; Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling
• Online Access: https://hdl.handle.net/10356/147995
• Institution: Nanyang Technological University

Coronaviruses (CoV) are a family of viruses that may cause respiratory diseases such as Middle East Respiratory Syndrome (MERS-CoV) and Severe Acute Respiratory Syndrome (SARS-CoV), and more recently CoVid-19. The genomic and proteomic data of these viruses from different labs are publicly available in various public data sources such as GenBank, EMBL and SwissProt etc. These data are dynamic and are regularly updated on public databases. They are analysed and research results are shared online to increase the speed and efficiency of pandemic research, potentially saving more lives. Bioinformatics tools are used to analyse biological data from these databases. This project details the implementation of biodeltaviz – a visual analytics tool on top of BiDel (A software which identifies differences in biological data) to analyze such data across different types of CoV as well as different versions of data within a specific type of CoV.