A tailored sparse PCA method for finding vaccine targets against Hepatitis C

Ahmed A. Quadeer, David Morales-Jimenez, Matthew R. McKay

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

We present a tailored sparse principal component analysis approach to identify parts of the Hepatitis C virus (HCV) proteome that may be particularly susceptible to immune pressure and thus may help in the design of an effective vaccine. Considering the highly data-limited HCV NS5B protein, the proposed method reveals two reasonably small sets of potentially vulnerable sites which can serve as new vaccine targets. The potential importance of the inferred sets of sites is emphasized through comparison with available clinical and biochemical data. Specifically, both groups of sites have functional significance, associated with viral replication, and one of the groups is found to be strongly targeted by immune systems of individuals who clear HCV naturally, without drugs.

Original languageEnglish
Title of host publication50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
PublisherIEEE Computer Society
Pages100-104
Number of pages5
ISBN (Electronic)9781538639542
DOIs
Publication statusPublished - 01 Mar 2017
Externally publishedYes
Event50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 - Pacific Grove, United States
Duration: 06 Nov 201609 Nov 2016

Conference

Conference50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
CountryUnited States
CityPacific Grove
Period06/11/201609/11/2016

ASJC Scopus subject areas

  • Signal Processing
  • Computer Networks and Communications

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  • Cite this

    Quadeer, A. A., Morales-Jimenez, D., & McKay, M. R. (2017). A tailored sparse PCA method for finding vaccine targets against Hepatitis C. In 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 (pp. 100-104). [7869002] IEEE Computer Society. https://doi.org/10.1109/ACSSC.2016.7869002