Rao Nini, Lei Xu, Guo Jianxiu, Huang Hao, Ren Zhenglong
School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan 610054, China.
Comput Biol Med. 2009 Apr;39(4):392-5. doi: 10.1016/j.compbiomed.2009.01.010. Epub 2009 Mar 17.
The sliding window is one of important factors that seriously affect the accuracy of coding region prediction and location for the methods based on power spectrum technique. It is very difficult to select the appropriate sliding step and the window length for different organisms. In this study, a novel sliding window strategy is proposed on the basis of power spectrum analysis for the accurate location of eukaryotic protein coding regions. The proposed sliding window strategy is very simple and the sliding step of window is changeable. Our tests show that the average location error for the novel method is 12 bases. Compared with the previous location error of 54 bases using the fixed sliding step, the novel sliding window strategy increased the location accuracy greatly. Further, the consumed CPU time to run the novel strategy is much shorter than the strategy of the fixed length sliding step. So, the computational complexity for the novel method is decreased greatly.
滑动窗口是严重影响基于功率谱技术的编码区预测和定位方法准确性的重要因素之一。为不同生物体选择合适的滑动步长和窗口长度非常困难。在本研究中,基于功率谱分析提出了一种新颖的滑动窗口策略,用于真核生物蛋白质编码区的精确定位。所提出的滑动窗口策略非常简单,窗口的滑动步长是可变的。我们的测试表明,该新方法的平均定位误差为12个碱基。与之前使用固定滑动步长时54个碱基的定位误差相比,新颖的滑动窗口策略大大提高了定位精度。此外,运行新策略所消耗的CPU时间比固定长度滑动步长策略要短得多。因此,新方法的计算复杂度大大降低。