Model-Based Optimization on DNA HEPG2
2.16Expected Top-1% ScoreGrad.Asc.
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| Grad.Asc.Number of generated designs=1000, Number of top designs for averaging=10, Number of runs=5, Score normalization method=min-max2024.10 | 2.16 | — | — | — | |
| TransformerNumber of generated designs=1000, Number of top designs for averaging=10, Number of runs=5, Score normalization method=min-max2024.10 | 2.13 | — | — | — | |
| CliqueformerNumber of generated designs=1000, Number of top designs for averaging=10, Number of runs=5, Score normalization method=min-max2024.10 | 2.1 | — | — | — | |
| IOMNumber of generated designs=1000, Number of top designs for averaging=10, Number of runs=5, Score normalization method=min-max2024.10 | 1.97 | — | — | — | |
| RWRNumber of generated designs=1000, Number of top designs for averaging=10, Number of runs=5, Score normalization method=min-max2024.10 | 1.91 | — | — | — | |
| DDOMNumber of generated designs=1000, Number of top designs for averaging=10, Number of runs=5, Score normalization method=min-max2024.10 | 1.82 | — | — | — | |
| MatchOptNumber of generated designs=1000, Number of top designs for averaging=10, Number of runs=5, Score normalization method=min-max2024.10 | 1.72 | — | — | — | |
| COMsNumber of generated designs=1000, Number of top designs for averaging=10, Number of runs=5, Score normalization method=min-max2024.10 | 1.2 | — | — | — | |
| Cliqueformer2024.10 | — | — | — | 2.1 | |
| COMs2024.10 | — | — | — | 1.2 | |
| DDOM2024.10 | — | — | — | 1.82 | |
| Grad.Asc.2024.10 | — | — | — | 2.16 | |
| IOM2024.10 | — | — | — | 1.97 | |
| MatchOpt2024.10 | — | — | — | 1.72 | |
| RWR2024.10 | — | — | — | 1.91 | |
| Transformer2024.10 | — | — | — | 2.13 |