Finding optimal finite biological sequences over finite alphabets: the OptiFin toolbox
This provides a user-friendly, modifiable toolbox for bioinformatics optimization problems, but it is incremental as it repackages existing methods.
The authors tackled the problem of finding optimal finite biological sequences over finite alphabets by developing the OptiFin toolbox, which embeds three well-known metaheuristics and performs very well on two difficult practical problems.
In this paper, we present a toolbox for a specific optimization problem that frequently arises in bioinformatics or genomics. In this specific optimisation problem, the state space is a set of words of specified length over a finite alphabet. To each word is associated a score. The overall objective is to find the words which have the lowest possible score. This type of general optimization problem is encountered in e.g 3D conformation optimisation for protein structure prediction, or largest core genes subset discovery based on best supported phylogenetic tree for a set of species. In order to solve this problem, we propose a toolbox that can be easily launched using MPI and embeds 3 well-known metaheuristics. The toolbox is fully parametrized and well documented. It has been specifically designed to be easy modified and possibly improved by the user depending on the application, and does not require to be a computer scientist. We show that the toolbox performs very well on two difficult practical problems.