首页> 外文期刊>Bioinformatics >Inference of biochemical network models in S-system using multiobjective optimization approach
【24h】

Inference of biochemical network models in S-system using multiobjective optimization approach

机译:基于多目标优化方法的S系统生化网络模型推断

获取原文
获取原文并翻译 | 示例
       

摘要

Motivation: The inference of biochemical networks, such as gene regulatory networks, protein–protein interaction networks, and metabolic pathway networks, from time-course data is one of the main challenges in systems biology. The ultimate goal of inferred modeling is to obtain expressions that quantitatively understand every detail and principle of biological systems. To infer a realizable S-system structure, most articles have applied sums of magnitude of kinetic orders as a penalty term in the fitness evaluation. How to tune a penalty weight to yield a realizable model structure is the main issue for the inverse problem. No guideline has been published for tuning a suitable penalty weight to infer a suitable model structure of biochemical networks.
机译:动机:从时程数据推断生物化学网络,例如基因调控网络,蛋白质-蛋白质相互作用网络和代谢途径网络,是系统生物学的主要挑战之一。推断建模的最终目标是获得能够定量理解生物系统每个细节和原理的表达式。为了推断可实现的S系统结构,大多数文章在适应性评估中应用了动力学阶数之和作为惩罚项。如何调整惩罚权重以产生可实现的模型结构是反问题的主要问题。尚未发布用于调整合适的罚分权重以推断生化网络的合适模型结构的指南。

著录项

  • 来源
    《Bioinformatics》 |2008年第8期|1085-1092|共8页
  • 作者单位

    Department of Chemical Engineering National Chung Cheng University Chiayi 621-02 Taiwan ROC;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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