We study a fundamental sequence algorithm arising from bioinformatics. Given two integers L and U and a sequence A of n numbers, the maximum-sum segment problem is to find a segment A[i,j] of A with L ≤ j-i+1 ≤ U that maximizes A[i]+A[i+1]+⋯+A[j]. The problem finds applications in finding repeats, designing low complexity filter, and locating segments with rich C+G content for biomolecular sequences. The best known algorithm, due to Lin, Jiang, and Chao, runs in O(n) time, based upon a clever technique called left-negative decomposition for A. In the present paper, we present a new O(n)-time algorithm that bypasses the left-negative decomposition. As a result, our algorithm has the capability to handle the input sequence in an online manner, which is clearly an important feature to cope with genome-scale sequences. We also show how to exploit the sparsity in the input sequence: If A is representable in O(k) space in some format, then our algorithm runs in O(k) time. Moreover, practical implementation of our algorithm running on the rice genome helps us to identify a very long repeat structure in rice chromosome 1 that is previously unknown. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Fan, T. H., Lee, S., Lu, H. I., Tsou, T. S., Wang, T. C., & Yao, A. (2003). An optimal algorithm for maximum-sum segment and its application in bioinformatics. Extended abstract. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2759, 251–257. https://doi.org/10.1007/3-540-45089-0_23
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