首页> 外文会议>IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology >Finding optimal finite biological sequences over finite alphabets: the OptiFin toolbox
【24h】

Finding optimal finite biological sequences over finite alphabets: the OptiFin toolbox

机译:在有限字母表中找到最佳有限生物序列:OPTIFIN工具箱

获取原文

摘要

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.
机译:在本文中,我们介绍了一个工具箱,用于经常在生物信息学或基因组学中产生的特定优化问题。在该特定的优化问题中,状态空间是有限字母表中指定长度的一组字。每个单词都与分数相关联。整体目标是找到具有最低分数的单词。这种类型的一般优化问题在例如蛋白质结构预测的3D构象优化中,或基于一组物种的最佳支持的系统发育树的最大核心基因子集发现。为了解决这个问题,我们提出了一个工具箱,可以使用MPI轻松推出,并嵌入3个着名的核心学。工具箱是完全参数化和良好的记录。它专门设计用于根据应用程序轻松修改,并且可能由用户改进,并且不需要成为计算机科学家。我们表明工具箱在两个艰难的实际问题上表现得非常好。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号