基于逻辑运算的离散人工蜂群优化双聚类算法

摘要

基因表达数据是由DNA微阵列实验产生的大规模数据矩阵,双聚类算法是挖掘数据矩阵中具有较高相关性的子矩阵,能有效地提取生物学信息。针对当前多目标双聚类优化算法易于陷入早熟和局部最优解等问题,论文提出了基于逻辑运算的离散人工蜂群优化双聚类算法(LOABCB算法),一方面引入人工蜂群算法增强双聚类的全局寻优能力,另一方面通过逻辑运算邻域搜索策略寻找最优双聚类,提高搜索效率。采用基因表达数据的酵母细胞数据集进行实验,结果表明论文算法能够获得实验效果优的具有生物意义的双聚类。Gene expression data is generated from the DNA microarray experiments of large data matrix,which can effectively extract the biological information.Aiming at the multi-objective optimization biclustering algorithm is easy to fall into the problem of premature convergence and local optimal solution,this paper proposes a discrete artificial bee colony optimization biclustering algo⁃rithm based on logical operation(LOABCB algorithm),on the one hand,artificial bee colony algorithm is introduced to enhance the global searching ability of biclustering,on the other hand through the logical operation neighborhood search strategy to find the optimal bicluster,the search efficiency is improved.evaluating the performance of the algorithm is a famous gene expression dataset of yeast cells based on data sets.The experimental results show that the algorithm can obtain biclusters with experimental effect and biological significance.

作者马卫朱娴MA Wei;ZHU Xian(School of Hotel Management,Nanjing Institute of Tourism and Hospitality,Nanjing 211100;State Key Laboratory for Novel Software Technology,Department of Computer Science&Technology,Nanjing University,Nanjing 210093;Department of Computer Science,Zijin College,Nanjing University of Science and Technology,Nanjing 210046)

机构地区南京旅游职业学院酒店管理学院南京大学计算机科学与技术系计算机软件新技术国家重点实验室南京理工大学紫金学院计算机学院

出处《计算机与数字工程》 2021年第3期433-438,共6页Computer & Digital Engineering

基金国家自然科学基金项目(编号:61272219,61321491) 国家863高技术研究发展计划(编号:2007AA01Z334) 江苏省科技计划(编号:BE2010072,BE2011058,BY2012190) 江苏省高校自然科学研究面上项目(编号:17KJB520013) 计算机软件新技术国家重点实验室创新基金重点项目(编号:ZZKT2018A09) 江苏省高校品牌专业建设工程项目(编号:PPZY2015A098)资助。

关键词基因表达数据双聚类逻辑运算离散人工蜂群算法gene expression data biclustering logical operation discrete artificial bee colony algorithm

分类号TP399 [自动化与计算机技术—计算机应用技术]