Research map / Learning theory and algorithms / Submodular and game algorithms
Constrained Submodular Optimization for Vaccine Design
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use Optivax-P instead of random peptide selection | Peptide vaccine selection · 2,000 randomly generated settings | objective score | Helped |
| Use Optivax-P instead of linear approximation | Peptide vaccine selection · 2,000 randomly generated settings | objective score | Helped |
| Select peptides with Optivax-P using the diminishing-returns objective | SARS-CoV-2 vaccine design · SARS-CoV-2 vaccine design | U5 objective | Helped |
| Optimize with Optivax-P's diminishing-returns objective rather than previous design approaches | 19-peptide vaccine designs · SARS-CoV-2 vaccine design, n-times coverage evaluation | n-times coverage | Mixed |
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