[Jongkees-group.beta] FW: Seminar Gunnar Klau (HHU Düsseldorf): Tue. 12 Dec., 14.00-15.00 h, O|2 Auditorium

[Jongkees, S.A.K. (Seino)]

Seino A. K. Jongkees, Ph.D.
Associate Professor
AIMMS Amsterdam Institute of Molecular and Life Sciences
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T +31 (0)6 5722 7168<tel:+31657227168> | http://sakjongkees.wixsite.com/website | s.a.k.jongkees at vu.nl<mailto:s.a.k.jongkees at vu.nl>
Vrije Universiteit Amsterdam, Chemistry and Pharmaceutical Sciences, O|2 building
O2-03W51, De Boelelaan 1108, 1081 HZ Amsterdam, The Netherlands

From: Geerke, D.P. (Daan) <d.p.geerke at vu.nl>
Date: Friday, 24 November 2023 at 15:43
To: Mouhib, H. (Halima) <h.mouhib at vu.nl>
Subject: Seminar Gunnar Klau (HHU Düsseldorf): Tue. 12 Dec., 14.00-15.00 h, O|2 Auditorium
Dear colleagues,

You are cordially invited to join the seminar of Gunnar Klau (professor for Algorithmic Bioinformatics at Heinrich Heine University, Düsseldorf, Germany) on Tue. 12 December at 14.00-15.00 h in the O|2 auditorium. He will talk about his combinatorial approach to SARS-CoV-2 peptide vaccine design. See below for the full details of his talk, including an abstract.
We hope to see you all, and please feel free to share this invitation with other potentially interested colleagues.

Kind regards, Halima Mouhib and Daan Geerke

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Speaker:  prof. dr. Gunnar Klau (Algorithmic Bioinformatics, Dept. Computer Science, HHU Düsseldorf, Germany)
Date:         Tue. 12 December, 14.00-15.00 h
Location: Auditorium O|2 building
Title:           A combinatorial approach to SARS-CoV-2 peptide vaccine design

Abstract:

Peptide vaccines present a safe and cost-efficient alternative to traditional vaccines. Their efficacy depends on the peptides included in the vaccine and the ability of major histocompatibility complex (MHC) molecules to bind and present these peptides. However, choosing a set of peptides that effectively achieve immunization across a large proportion of the population is challenging.

We present HOGVAX, a population-coverage-optimizing combinatorial approach to peptide vaccine design. Uniquely, HOGVAX exploits overlaps between peptides to increase the number of peptides encoded in limited space, thereby enabling consideration of rare MHC alleles. We formalize the vaccine design task as a theoretical problem, which we call the Maximum Scoring k-Superstring Problem (MSKS). We show that MSKS is NP-hard, and reformulate it into a graph problem using the hierarchical overlap graph (HOG). We give an integer linear programming formulation for the graph problem and provide an open source implementation.
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