Abstract
We address the issue of approximating the 2-Interval Pattern problem over its various models and restrictions. This problem, motivated by RNA secondary structure prediction, asks to find a maximum cardinality subset of a 2-interval set with respect to some prespecified geometric constraints. We present several constant factor approximation algorithms whose performance guarantee depends on the different possible restrictions imposed on the input 2-interval set. In addition, we show that our results extend to the weighted variant of the problem.
Original language | English |
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Pages (from-to) | 283-297 |
Number of pages | 15 |
Journal | Theoretical Computer Science |
Volume | 395 |
Issue number | 2-3 |
State | Published - 1 May 2008 |
Externally published | Yes |
Bibliographical note
Funding Information:The authors would like to express their gratitude to Martin C. Golumbic for the fruitful discussions and valuable remarks. The first author was partially supported by CNRS, France, and the French Ministry of Research through ACI NIM. The third author was partially supported by the Israel Science Foundation grant 35/05.
Funding
The authors would like to express their gratitude to Martin C. Golumbic for the fruitful discussions and valuable remarks. The first author was partially supported by CNRS, France, and the French Ministry of Research through ACI NIM. The third author was partially supported by the Israel Science Foundation grant 35/05.
Funders | Funder number |
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ACI NIM | |
French Ministry of Research | |
Israel Science Foundation | 35/05 |
Centre National de la Recherche Scientifique |
Keywords
- 2-interval
- Combinatorial approximation algorithms
- RNA secondary structure prediction