吉林大学学报(理学版)

• 计算机科学 • 上一篇    下一篇

基于灰值区间的微阵列模拟数据生成算法

夏雪飞1,2, 韩啸3, 兰天姝1, 王礼华4, 吴佳楠5, 周柚1   

  1. 1. 吉林大学 计算机科学与技术学院, 长春 130012; 2. 吉林交通职业技术学院 电子信息学院, 长春 130012;3. 吉林大学 学报编辑部, 长春 130012; 4. 大阪电气通信大学 信息科学与艺术学院, 日本 大阪 5750063;5. 长春大学 计算机科学技术学院, 长春 130022
  • 收稿日期:2016-07-26 出版日期:2016-11-26 发布日期:2016-11-29
  • 通讯作者: 周柚 E-mail:zyou@jlu.edu.cn

An Algorithm for Generation of Simulated MicroarrayData Based on Grey Value Interval

XIA Xuefei1,2, HAN Xiao3, LAN Tianshu1, WANG Lihua4, WU Jianan5, ZHOU You1   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China;2. College of Electronic Information, Jilin Communications Polytechnic College, Changchun 130012, China;3. Editorial Department of Journal of Jilin University, Changchun 130012, China;4. Faculty of Information Science and Arts, Osaka ElectroCommunication University, Osaka 5750063, Japan;5. College of Computer Science and Technology, Changchun University, Changchun 130022, China
  • Received:2016-07-26 Online:2016-11-26 Published:2016-11-29
  • Contact: ZHOU You E-mail:zyou@jlu.edu.cn

摘要: 针对微阵列芯片数据采集量大、 获取成本高的问题, 提出一种新的基于灰值区间的微阵列模拟数据生成算法. 该算法通过灰值度量的方式模拟微阵列数据中基因的差异表达属性, 结合聚类分析方法创建聚类隧道, 进而产生与原始数据具有相似数理分布及生物学意义的模拟数据. 采用模拟数据和真实生物数据对算法进行实验验
证与分析, 实验结果表明, 基于灰值区间理念与聚类隧道产生机制生成的模拟数据是有效且可靠的.

关键词: 模拟数据, 聚类分析, 差异表达基因, 微阵列数据, 样本

Abstract: Aiming at the problem of large data acquisition and high cost of microarray chip, we proposed a new algorithm for generation of simulated microarray data based on grey value interval. The algorithm simulated differential expression of genes in microarray data by means of grey value measurement, combined with cluster analysis method to create a cluster tunnel, and then generated simulation data with similar mathematical distribution and biological significance of the original data. The algorithm was verified and analyzed by simulated data and real biological data. Experimental results show that the simulation data generated by the concept of grey value interval and the generation mechanism of cluster tunnel is effective and reliable.

Key words: simulated data, cluster analysis, differentially expressed genes, microarray data, sample

中图分类号: 

  • TP393