Paper Info
Title
The simplified partial digest problem: Approximation and a graph-theoretic model
Abstract
The goal of the simplified partial digest problem (SPDP) is motivated by the reconstruction of the linear structure of a DNA chain with respect to a given nucleotide pattern, based on the multiset of distances between the adjacent patterns (interpoint distances) and the multiset of distances between each pattern and the two unlabeled endpoints of the DNA chain (end distances). We consider optimization versions of the problem, called SPDP-Min and SPDP-Max. The aim of SPDP-Min (SPDP-Max) is to find a DNA linear structure with the same multiset of end distances and the minimum (maximum) number of incorrect (correct) interpoint distances. Results are presented on the worst-case efficiency of approximation algorithms for these problems. We suggest a graph-theoretic model for SPDP-Min and SPDP-Max, which can be used to reduce the search space for an optimal solution in either of these problems. We also present heuristic polynomial time algorithms based on this model. In computational experiments with randomly generated and real-life input data, our best algorithm delivered an optimal solution in 100% of the instances for a number of restriction sites not greater than 50.
Year
DOI
Venue
2011
10.1016/j.ejor.2010.07.027
European Journal of Operational Research
Keywords
Field
DocType
Integer programming,Genome mapping,Combinatorial optimization,Heuristics,Approximation algorithms
Graph theory,Approximation algorithm,Mathematical optimization,Combinatorics,Heuristic,Multiset,Multiplicity (mathematics),Algorithm,Combinatorial optimization,Integer programming,Time complexity,Mathematics
Journal
Volume
Issue
ISSN
208
2
0377-2217
Citations 
PageRank 
References 
0
0.34
19
Authors
5
Name
Order
Citations
PageRank
Jacek Blazewicz11064154.23
Edmund K. Burke25593363.80
Marta Kasprzak330629.54
Alexandr Kovalev4122.34
Mikhail Y. Kovalyov51602118.18