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Massachusetts Institute of Technology

Identification of reassortant influenza viruses at scale : algorithm and applications

Abstract

dc:description.abstract

Reassortment is a reticulate evolutionary process that results in genome shuffling; the most prominent virus known to reassort is the influenza A virus. Methods to identify reassortant influenza viruses do not scale well beyond hundreds of isolates at a time, because they rely on phylogenetic reconstruction, a computationally expensive method. This thus hampers our ability to test systematically whether reassortment is associated with host switching events. In this thesis, I use phylogenetic heuristics to develop a new reassortment detection algorithm capable of finding reassortant viruses in tens of thousands viral isolates. Together with colleagues, we then use the algorithm to test whether reassortment events are over-represented in host switching events and whether reassortment is an alternative 'transmission strategy' for viral persistence.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Biological Engineering.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Ma, Eric J. (Eric Jinglong)
Advisor dc:contributor.advisor
  • Jonathan A. Runstadler.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/112387
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/112387

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Ma, Eric J. (Eric Jinglong). Identification of reassortant influenza viruses at scale : algorithm and applications. Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112387