Machine Learning Benchmark for Reductase Substrate Activation: This repository presents a systematic approach to evaluate a comprehensive set of features for predicting activation free energy, specifically focusing on kcat values. The benchmark model automates the process, ensuring rigorous and reproducible results in substrate energy screening.
active 2023-09-29 → 2023-09-29 (UTC)
Activity over time
Daily event counts in the loaded window
Line chart, 1 days from 2023-09-29 to 2023-09-29. Pushes: 1 total, peak 1 in a day. Pull requests: 2 total, peak 2 in a day. Issues: 0 total, peak 0 in a day. Comments: 0 total, peak 0 in a day. Stars: 0 total, peak 0 in a day.
- Pushes
- Pull requests
- Issues
- Comments
- Stars
Top contributors
Pushes, PRs, issues, reviews and comments — stars and forks excluded, so this is contribution rather than popularity
| Contributor | Contributions | Pushes | PRs | Comments |
|---|---|---|---|---|
| bryankappa | 3 | 1 | 2 | 0 |
Recent activity
Latest issues, pull requests and releases
- Pull request#2bryankappa2023-09-29 07:28
- Pull request#2bryankappa2023-09-29 07:28
Totals cover only the window loaded into ClickHouse and count events, not GitHub's lifetime totals — 0 stars here means stars gained during the window, not the repo's star count.