Mathematically Rigorous Results In Sequence Matching.

BLAST程序（BLASTP， PSI-BLAST等）目前使用离线计算机模拟来准确估计序列匹配的统计显著性。这个项目已经将离线计算机模拟的速度提高了100-1000倍。它的最终目标是进一步加快模拟的速度，这样它们就可以通过网络在线完成。如果项目成功，BLAST用户将可以自由地使用他们选择的任何分数和惩罚来匹配序列。在序列匹配统计中有两个参数：尺度参数？lambda？前因子k。我们启发式地推导出尺度参数的新方程。这个方程可以估计？高效率、高精度。此外，我们还提出了几个新的Gumbel前因子？k？基于路径反转恒等式和泊松聚类启发式算法。这个公式也提供了非常精确的结果。在下一步中，我们将探索统计数据的边缘效应。在序列匹配概率的渐近展开式中，具有有限长度的实序列作为校正项出现，因而存在边缘效应。这种边缘效应在有间隙匹配的统计数据中可能比在没有间隙匹配的统计数据中更重要，因为有间隙匹配往往更长，更容易耗尽匹配的序列。

The BLAST programs (BLASTP, PSI-BLAST, etc.) presently use offline computer simulations to give accurate estimates of statistical significance for sequence matches. This project has already speeded those offline computer simulations by a factor of 100-1000. Its eventual aim is to speed the simulations further, so they can be done online over the web. If the project is successful, BLAST users will then be free to use any scores and penalties they choose for matching sequences. There are two parameters in sequence matching statistics: the scale parameter ?lambda? and the pre-factor ?k?. We heuristically derived the new equation for scale parameter ?lambda?. This equation can estimate ?lambda? efficiently with high accuracy. In addition, we have proposed several new formulas for Gumbel pre-factor ?k? based on the path reversal identity and the Poisson clumping heuristic. This formula also provides very accurate results. In our next step, we will explore edge effects on the statistics. Edge effects are present because real sequences have limited lengths appear as a correction term in an asymptotic expansion of the probability of sequence matching. This edge effect is likely to be more important in the statistics of matching with gaps than it was in the statistics of matching without gaps, because gapped matches tend to be longer, exhausting the sequences being matched more easily.