Among the sequence selection and comparison problems, the Far From Most String Problem (FFMSP) is one of the computationally hardest with applications in several fields, including molecular biology where one is interested in creating diagnostic probes for bacterial infections or in discovering potential drug targets. In this article, several hybrid metaheuristics are described and tested. Extensive comparative experiments on a large set of randomly generated test instances indicate that these randomized hybrid techniques are both effective and efficient. © 2013 Springer-Verlag.
Hybrid metaheuristics for the far from most string problem
Ferone D.;
2013-01-01
Abstract
Among the sequence selection and comparison problems, the Far From Most String Problem (FFMSP) is one of the computationally hardest with applications in several fields, including molecular biology where one is interested in creating diagnostic probes for bacterial infections or in discovering potential drug targets. In this article, several hybrid metaheuristics are described and tested. Extensive comparative experiments on a large set of randomly generated test instances indicate that these randomized hybrid techniques are both effective and efficient. © 2013 Springer-Verlag.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
