Online analytics for host-pathogen protein interactions analysis

As Influenza A virus (IAV) is a significant danger to global human health and life, it is critical to have a deeper knowledge of the virulence factors responsible for IAV infections to counteract potential outbreaks. A reliable analytical tool requires dependable data. This project started with data...

Full description

Saved in:
Bibliographic Details
Main Author: Ng, Teng Ann
Other Authors: Kwoh Chee Keong
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/153211
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-153211
record_format dspace
spelling sg-ntu-dr.10356-1532112021-11-16T06:02:04Z Online analytics for host-pathogen protein interactions analysis Ng, Teng Ann Kwoh Chee Keong School of Computer Science and Engineering ASCKKWOH@ntu.edu.sg Engineering::Computer science and engineering As Influenza A virus (IAV) is a significant danger to global human health and life, it is critical to have a deeper knowledge of the virulence factors responsible for IAV infections to counteract potential outbreaks. A reliable analytical tool requires dependable data. This project started with data collection, where records of IAV infections from experiments conducted in mice were collected from numerous literature searches to conduct a meta-analysis, to deliver more accurate insights and offer adequate confidence on the viral factors accountable for the extreme harmfulness of IAV infections. Additionally, host-pathogen protein interaction analysis is intensified by the fact that an average protein consists of two or more domains, which are structurally and evolutionary independent subunits. As each domain has its distinct structure and biological function, only a selected subset of domains constituting each protein are involved in an interaction between a pair of proteins. Thus, superfamily domains from IAV and mouse proteins involved in host-pathogen protein interactions must be uncovered. Finally, a Graphical User Interface (GUI) was implemented to present all collected data, particularly, the virulence classification labels for records of IAV infections and to display interacting IAV-mouse protein domains as a network of nodes. Bachelor of Engineering (Computer Science) 2021-11-16T06:02:03Z 2021-11-16T06:02:03Z 2021 Final Year Project (FYP) Ng, T. A. (2021). Online analytics for host-pathogen protein interactions analysis. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/153211 https://hdl.handle.net/10356/153211 en SCSE20-0973 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering
spellingShingle Engineering::Computer science and engineering
Ng, Teng Ann
Online analytics for host-pathogen protein interactions analysis
description As Influenza A virus (IAV) is a significant danger to global human health and life, it is critical to have a deeper knowledge of the virulence factors responsible for IAV infections to counteract potential outbreaks. A reliable analytical tool requires dependable data. This project started with data collection, where records of IAV infections from experiments conducted in mice were collected from numerous literature searches to conduct a meta-analysis, to deliver more accurate insights and offer adequate confidence on the viral factors accountable for the extreme harmfulness of IAV infections. Additionally, host-pathogen protein interaction analysis is intensified by the fact that an average protein consists of two or more domains, which are structurally and evolutionary independent subunits. As each domain has its distinct structure and biological function, only a selected subset of domains constituting each protein are involved in an interaction between a pair of proteins. Thus, superfamily domains from IAV and mouse proteins involved in host-pathogen protein interactions must be uncovered. Finally, a Graphical User Interface (GUI) was implemented to present all collected data, particularly, the virulence classification labels for records of IAV infections and to display interacting IAV-mouse protein domains as a network of nodes.
author2 Kwoh Chee Keong
author_facet Kwoh Chee Keong
Ng, Teng Ann
format Final Year Project
author Ng, Teng Ann
author_sort Ng, Teng Ann
title Online analytics for host-pathogen protein interactions analysis
title_short Online analytics for host-pathogen protein interactions analysis
title_full Online analytics for host-pathogen protein interactions analysis
title_fullStr Online analytics for host-pathogen protein interactions analysis
title_full_unstemmed Online analytics for host-pathogen protein interactions analysis
title_sort online analytics for host-pathogen protein interactions analysis
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/153211
_version_ 1718368031978029056