An Experimental and Theoretical Comparison of Model SelectionMethods
Machine Learning - Special issue on the eighth annual conference on computational learning theory, (COLT '95)
Programming pearls: algorithm design techniques
Communications of the ACM
Journal of Computer and System Sciences - Computational biology 2002
A Linear Time Algorithm for Finding All Maximal Scoring Subsequences
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
The minimum description length principle in coding and modeling
IEEE Transactions on Information Theory
Segmentation with an isochore distribution
WABI'06 Proceedings of the 6th international conference on Algorithms in Bioinformatics
Computing maximum-scoring segments in almost linear time
COCOON'06 Proceedings of the 12th annual international conference on Computing and Combinatorics
Finding maximum sum segments in sequences with uncertainty
ISAAC'11 Proceedings of the 22nd international conference on Algorithms and Computation
Journal of Discrete Algorithms
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We examine the problem of finding maximum-scoring 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 noncoding RNA genes in thermophiles.