K-d trees for semidynamic point sets
SCG '90 Proceedings of the sixth annual symposium on Computational geometry
Sparse dynamic programming I: linear cost functions
Journal of the ACM (JACM)
Trapezoid graphs and generalizations, geometry and algorithms
Discrete Applied Mathematics
Chaining multiple-alignment fragments in sub-quadratic time
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Longest Common Subsequence from Fragments via Sparse Dynamic Programming
ESA '98 Proceedings of the 6th Annual European Symposium on Algorithms
EMAGEN: an efficient approach to multiple whole genome alignment
APBC '04 Proceedings of the second conference on Asia-Pacific bioinformatics - Volume 29
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Given a set of weighted hyper-rectangles in a k-dimensional space, the chaining problem is to identify a set of colinear and nonoverlapping hyper-rectangles of total maximal weight. This problem is used in a number of applications in bioinformatics, string processing, and VLSI design. In this paper, we present parallel versions of the chaining algorithm for bioinformatics applications, running on multi-core and computer cluster architectures. Furthermore, we present experimental results of our implementations on both architectures.