RoseTTAFold
基于三轨注意力网络的蛋白质结构预测方法，同时建模序列、距离图和三维坐标之间的信息传递。 该方法在较低计算成本下实现了接近 AlphaFold 的预测精度，推动了结构预测模型的快速普及。
| Property | Value |
|---|---|
| Purpose | 基于多轨神经网络的高精度蛋白质结构预测 |
| Time Complexity | O(n^2) |
| Space Complexity | O(n^2) |
| Year | 2021 |
| Category | Protein Structure Prediction |
Complexity Analysis
- Time Complexity:
O(n^2) - Space Complexity:
O(n^2)
Performance Insight: The time complexity of this algorithm is quadratic (O(n²)), suitable for moderate data sizes; consider approximation algorithms for large inputs. 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
AlphaFold · ESMFold · trRosetta