Glimmer
基于插值马尔可夫模型的微生物基因发现工具，通过从训练序列中学习编码区统计特征高效识别开放阅读框。 该方法是原核基因预测领域的经典算法，在完整基因组和草图组装中都能提供可靠的基因边界和起始位点预测。
| Property | Value |
|---|---|
| Purpose | 原核基因组的开放阅读框和基因边界预测 |
| Time Complexity | O(n) |
| Space Complexity | O(n) |
| Year | 1998 |
| Difficulty | Intermediate |
| Languages | C |
| Category | Gene Prediction |
Complexity Analysis
- Time Complexity:
O(n) - Space Complexity:
O(n)
Performance Insight: The time complexity of this algorithm is linear (O(n)), scales linearly to TB-scale data and is suitable for streaming pipelines. Linear space can often be reduced by constant factors via sliding-window techniques.
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
Prodigal · GeneMark · FragGeneScan