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

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

doi:10.1109/ACSSC.2016.7869002

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 proceeding › Conference 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 language	English
Title of host publication	50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	100-104
Number of pages	5
ISBN (Electronic)	9781538639542
DOIs	https://doi.org/10.1109/ACSSC.2016.7869002
Publication status	Published - 01 Mar 2017
Externally published	Yes
Event	50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016 - Pacific Grove, United States Duration: 06 Nov 2016 → 09 Nov 2016

Conference

Conference	50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016
Country/Territory	United States
City	Pacific Grove
Period	06/11/2016 → 09/11/2016

ASJC Scopus subject areas

Signal Processing
Computer Networks and Communications

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/ACSSC.2016.7869002Licence: Unspecified

Cite this

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title = "A tailored sparse PCA method for finding vaccine targets against Hepatitis C",

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.",

author = "Quadeer, {Ahmed A.} and David Morales-Jimenez and McKay, {Matthew R.}",

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doi = "10.1109/ACSSC.2016.7869002",

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Quadeer, AA, Morales-Jimenez, D & McKay, MR 2017, A tailored sparse PCA method for finding vaccine targets against Hepatitis C. in 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016., 7869002, Institute of Electrical and Electronics Engineers Inc., pp. 100-104, 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016, Pacific Grove, United States, 06/11/2016. https://doi.org/10.1109/ACSSC.2016.7869002

A tailored sparse PCA method for finding vaccine targets against Hepatitis C. / Quadeer, Ahmed A.; Morales-Jimenez, David; McKay, Matthew R.
50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016. Institute of Electrical and Electronics Engineers Inc., 2017. p. 100-104 7869002.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - A tailored sparse PCA method for finding vaccine targets against Hepatitis C

AU - Quadeer, Ahmed A.

AU - Morales-Jimenez, David

AU - McKay, Matthew R.

PY - 2017/3/1

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N2 - 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.

AB - 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.

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DO - 10.1109/ACSSC.2016.7869002

M3 - Conference contribution

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EP - 104

BT - 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 50th Asilomar Conference on Signals, Systems and Computers, ACSSC 2016

Y2 - 6 November 2016 through 9 November 2016

ER -

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

Abstract

Conference

ASJC Scopus subject areas

UN SDGs

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