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中文摘要：
相同察觉在生物信息学起一个关键作用，而替换矩阵是在相同察觉的最重要的部件之一。因此除排列算法的改进以外，提高相同察觉的精确性的另一个有效方法是篷乱合适的替换矩阵或甚至构造新矩阵。各种各样的矩阵的特征上并且在在在相同察觉的不同矩阵之间的表演的比较上的研究使我们能为一些特定的应用程序选择最合适或最佳的矩阵。在这篇论文，由作为一个例子拿 BLOSUM 矩阵，在相同察觉的矩阵的一些详细特征被在不同顺序身份和顺序长度上计算公认的蛋白质的数字的分布学习。我们的结果清楚地证明不同矩阵有到遥远的相应蛋白质的识别的不同偏爱和能力。而且，详细说明了各种各样的矩阵的特征能被用来改进相同的精确性察觉。
英文摘要：
Homology detection plays a key role in bioinformatics, whereas substitution matrix is one of the most important components in homology detection. Thus, besides the improvement of alignment algorithms, another effective way to enhance the accuracy of homology detection is to use proper substitution matrices or even construct new matrices. A study on the features of various matrices and on the comparison of the performances between different matrices in homology detection enable us to choose the most proper or optimal matrix for some specific applications. In this paper, by taking BLOSUM matrices as an example, some detailed features of matrices in homology detection are studied by calculating the distributions of numbers of recognized proteins over different sequence identities and sequence lengths. Our results clearly showed that different matrices have different preferences and abilities to the recognition of remote homologous proteins. Furthermore, detailed features of the various matrices can be used to improve the accuracy of homology detection.
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