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微阵列数据的双聚类迭代局部搜索

Iterated Local Search for Biclustering of Microarray Data
课程网址: http://videolectures.net/prib2010_ayadi_ilsb/  
主讲教师: Wassim Ayadi
开课单位: 昂热大学
开课时间: 2010-10-14
课程语种: 英语
中文简介:
在微阵列数据分析的背景下,双聚集旨在同时识别一组在一组实验条件下高度相关的基因。针对微阵列数据的双聚类问题,提出了一种双聚类迭代局部搜索算法。利用新的评价函数、专用的邻域关系和定制的摄动策略等原始特征,突出了该算法的优越性。在已知的酵母细胞周期数据集上对BILS算法进行了评估,并与两种最常用的算法进行了比较。
课程简介: In the context of microarray data analysis, biclustering aims to identify simultaneously a group of genes that are highly correlated across a group of experimental conditions. This paper presents a Biclustering Iterative Local Search (BILS) algorithm to the problem of biclustering of microarray data. The proposed algorithm is highlighted by the use of some original features including a new evaluation function, a dedicated neighborhood relation and a tailored perturbation strategy. The BILS algorithm is assessed on the well-known yeast cell-cycle dataset and compared with two most popular algorithms.
关 键 词: 微阵列数据分析; 迭代局部搜索; 红麻算法; 循环数据集
课程来源: 视频讲座网
最后编审: 2020-06-02:张荧(课程编辑志愿者)
阅读次数: 39