ProGen
基于条件语言模型的蛋白质序列生成方法，可按指定的功能标签和结构条件 生成具有目标属性的新蛋白质序列。该方法生成的序列具有天然蛋白的特性， 可通过实验验证其功能。
| Property | Value |
|---|---|
| Purpose | 条件可控的蛋白质序列生成 |
| Time Complexity | O(n^2 * d) |
| Space Complexity | O(n^2) |
| Year | 2020 |
| Difficulty | Advanced |
| Languages | Python |
| Category | Protein Language Model |
Complexity Analysis
- Time Complexity:
O(n^2 * d) - Space Complexity:
O(n^2)
Performance Insight: The time complexity of this algorithm is polynomial. High space complexity; consider Hirschberg-style space-optimized variants for very long sequences.
Note: Complexity analysis is based on theoretical models. Actual runtime is affected by input scale, hardware, and implementation optimizations. Benchmark for your specific workload.
Literature & Implementation
Related Tools
ProteinMPNN · RFdiffusion · ESM
Tags
generative protein-design conditional-generation transformer