Towards a highly scalable hybrid metaheuristic for haplotype inference under parsimony

التفاصيل البيبلوغرافية
العنوان: Towards a highly scalable hybrid metaheuristic for haplotype inference under parsimony
المؤلفون: S. Benedettini, L. Di Gaspero, ROLI, ANDREA
المساهمون: F. XHAFA, F. HERRERA, A. ABRAHAM, M. KÖPPEN, J.M. BÉNITEZ, Benedettini, S., Di Gaspero, L., Roli, Andrea
بيانات النشر: IEEE Computer Society Press
USA
s.l
سنة النشر: 2008
المجموعة: IRIS Università degli Studi di Bologna (CRIS - Current Research Information System)
مصطلحات موضوعية: HYBRID METAHEURISTICS, HAPLOTYPE INFERENCE
الوصف: Haplotype inference is a challenging problem in bioinformatics that consists in inferring the basic genetic constitution of diploid organisms on the basis of their genotype. This piece of information allows researchers to perform association studies for the genetic variants involved in diseases and the individual responses to therapeutic agents. A notable approach to the problem is to encode it as a combinatorial problem (under certain hypotheses, such as the pure parsimony) and to solve it using off-the-shelf combinatorial optimization techniques. In this paper, we present and discuss an approach based on hybridization of two metaheuristics, one being a population based learning algorithm and the other a local search. We test our approach by solving instances from common Haplotype inference benchmarks. Results show that this approach achieves an improvement on solution quality with respect to the application of a single pure algorithm.
نوع الوثيقة: conference object
وصف الملف: STAMPA
اللغة: English
Relation: info:eu-repo/semantics/altIdentifier/isbn/9780769533261; ispartofbook:Eighth International Conference Hybrid Intelligent Systems; 8th International Conference on Hybrid Intelligent Systems; firstpage:702; lastpage:707; numberofpages:6; alleditors:F. XHAFA, F. HERRERA, A. ABRAHAM, M. KÖPPEN, J.M. BÉNITEZ; http://hdl.handle.net/11585/62717; info:eu-repo/semantics/altIdentifier/scopus/2-s2.0-55349106231
الاتاحة: http://hdl.handle.net/11585/62717
رقم الانضمام: edsbas.124D4FAA
قاعدة البيانات: BASE