MAVG: locating non-overlapping maximum average segments
in a given sequence

Lin, Yaw-Ling; Huang, Xiaoqiu; Jiang, Tao; Chao, Kun-Mao

doi:10.1093/bioinformatics/19.1.151

Cited by 36 publications

(22 citation statements)

References 6 publications

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“…Lin et al [36] give an algorithm that finds a segment with maximum average score of some minimum length L in O(n log L) time. The algorithm can be employed to find a chain of covers in which segments have large average scores [37].…”

Section: Discussionmentioning

confidence: 99%

Maximum-scoring segment sets

Csűrös

2004

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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Abstract-We examine the problem of finding maximumscoring sets of disjoint segments in a sequence of scores. The problem arises in DNA and protein segmentation, and in postprocessing of sequence alignments. Our key result states a simple recursive relationship between maximum-scoring segment sets. The statement leads to fast algorithms for finding such segment sets. We apply our methods to the identification of non-coding RNA genes in thermophiles.

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Section: Discussionmentioning

confidence: 99%

Maximum-scoring segment sets

Csűrös

2004

IEEE/ACM Trans. Comput. Biol. and Bioinf.

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“…Blum, Floyd, Pratt, Rivest, and Tarjan [2] gave an optimal O(n) time deterministic algorithm. The density selection problem such that k is equal to the total number of feasible segments is exactly the extensively studied maximum-density segment problem [4,10,12,14,15,18,20] which arises from the problem of finding the biologically meaningful region, called the most GC-ratio region, in a DNA sequence. When we let the input sequence A = (a 1 , w 1 ), (a 2 , w 2 ), .…”

Section: The Width W(i J) Of Segment A(i J) Ismentioning

confidence: 99%

Optimal Randomized Algorithm for the Density Selection Problem

Lin

Lee

2009

Algorithms and Computation

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Abstract. In the paper we consider a generalized version of three wellknown problems: Selection Problem in computer science, Slope Selection Problem in computational geometry and Maximum-Density Segment Problem in bioinformatics. Given a sequence A = (a1, w1), (a2, w2), . . . , (an, wn) of n ordered pairs (ai, wi) of real numbers ai and wi > 0 for each 1 ≤ i ≤ n, two nonnegative real numbers , u with ≤ u

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“…We may achieve a judicious tradeoff by selecting segments in order of nonincreasing density, where the density of a segment is defined as the average score of track points in that segment. It is possible to use recent work on efficient computation of maximum-density substrings for this purpose [18], [17], [13], [19].…”

Section: Related Workmentioning

confidence: 99%

Segment-Based Map Matching

Chawathe

2007

2007 IEEE Intelligent Vehicles Symposium

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Abstract-We address the problem of determining the path of a vehicle on a given vector map of roads, based on tracking data such as that obtained from onboard GPS receivers. We describe a method that is based on a piecewise matching of track segments to map features. A notable feature of our method is that it is applicable to a large class of existing methods. We discuss metrics for evaluating the output of map-matching methods and briefly describe our implementation of a mapmatching system based on our methods.

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MAVG: locating non-overlapping maximum average segments in a given sequence

Abstract: http://iubio.bio.indiana.edu/soft/molbio/pattern/cpg_islands/.

Cited by 36 publications

References 6 publications

Maximum-scoring segment sets

Maximum-scoring segment sets

Optimal Randomized Algorithm for the Density Selection Problem

Segment-Based Map Matching

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