An Algorithm for Frequent Pattern Mining in Biological Networks

ZHAO Jian-bang; DONG An-guo; GAO Lin

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An Algorithm for Frequent Pattern Mining in Biological Networks

更新时间：2025-07-16

- An Algorithm for Frequent Pattern Mining in Biological Networks
- Acta Electronica Sinica Vol. 38, Issue 8, Pages: 1803-1807(2010)
- 作者机构：
  
  1. 西安电子科技大学计算机学院,陕西,西安,710071
  2. 长安大学理学院,陕西,西安,710064
  3. 西安电子科技大学计算机学院陕西西安,710071
  4. 长安大学理学院陕西西安,710064
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP311.12
- Published：2010
- 稿件说明：
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ZHAO Jian-bang, DONG An-guo, GAO Lin. An Algorithm for Frequent Pattern Mining in Biological Networks[J]. Acta Electronica Sinica, 2010, 38(8): 1803-1807.
DOI：

ZHAO Jian-bang, DONG An-guo, GAO Lin. An Algorithm for Frequent Pattern Mining in Biological Networks[J]. Acta Electronica Sinica, 2010, 38(8): 1803-1807. DOI：

摘要

频繁模式挖掘是生物网络数据分析中的一个核心问题

对于研究生物网络的组织结构和功能模块具有重要意义.本文提出了子图环分布的概念并构造了子图搜索算法

提高了搜索效率.其次设计了动态抽样算法计算子图频率

用于提高非穷举搜索的精度.利用4个真实生物网络数据进行仿真实验研究

验证了本文算法在效率和精度上相对于现有算法的优势.

Abstract

Frequent pattern mining has emerged as a key issue for analyzing the biological networks since it gives us insights into the organism and functional modules.A novel algorithm for this problem is proposed

which can efficiently obtain all these frequent subgraphs in networks based on the distribution of ring.To improve the accuracy of subgraph mining in non-exhaustive enumerate mode

additionally

we provide a dynamic sample algorithm.The experimental results in four real bio-networks show the superiority of our algorithm to existing algorithms.

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