A statistical theory of sequence alignment with gaps.

D Drasdo, T Hwa, M Lässig
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Abstract

A statistical theory of local alignment algorithms with gaps is presented. Both the linear and logarithmic phases, as well as the phase transition separating the two phases, are described in a quantitative way. Markov sequences without mutual correlations are shown to have scale-invariant alignment statistics. Deviations from scale invariance indicate the presence of mutual correlations detectable by alignment algorithms. Conditions are obtained for the optimal detection of a class of mutual sequence correlations.

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带间隙序列比对的统计理论。
提出了一种具有间隙的局部对齐算法的统计理论。线性相和对数相,以及将这两相分离的相变,都以定量的方式进行了描述。没有相互关联的马尔可夫序列被证明具有尺度不变的排列统计。偏离尺度不变性表明存在可通过对准算法检测到的相互相关性。得到了一类互序列相关性的最优检测条件。
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