MAXIMUM n-TIMES COVERAGE FOR VACCINE DESIGN
10th International Conference on Learning Representations, ICLR 2022
; 2022.
Article
in English
| Scopus | ID: covidwho-2269276
ABSTRACT
We introduce the maximum n-times coverage problem that selects k overlays to maximize the summed coverage of weighted elements, where each element must be covered at least n times. We also define the min-cost n-times coverage problem where the objective is to select the minimum set of overlays such that the sum of the weights of elements that are covered at least n times is at least τ. Maximum n-times coverage is a generalization of the multi-set multi-cover problem, is NP-complete, and is not submodular. We introduce two new practical solutions for n-times coverage based on integer linear programming and sequential greedy optimization. We show that maximum n-times coverage is a natural way to frame peptide vaccine design, and find that it produces a pan-strain COVID-19 vaccine design that is superior to 29 other published designs in predicted population coverage and the expected number of peptides displayed by each individual's HLA molecules. © 2022 ICLR 2022 - 10th International Conference on Learning Representationss. All rights reserved.
Search on Google
Collection:
Databases of international organizations
Database:
Scopus
Topics:
Vaccines
Language:
English
Journal:
10th International Conference on Learning Representations, ICLR 2022
Year:
2022
Document Type:
Article
Similar
MEDLINE
...
LILACS
LIS