Title page for etd-0320112-103212


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URN etd-0320112-103212
Author Shan-Hao He
Author's Email Address thelegendoffancyrealm@gmail.com
Statistics This thesis had been viewed 5646 times. Download 346 times.
Department Information Management
Year 2011
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title A Boolean knowledge-based approach to assist reconstruction of gene regulatory model
Date of Defense 2012-01-12
Page Count 76
Keyword
  • System Biology
  • Reverse Engineering
  • Gene Regulatory networks
  • S-system
  • Boolean networks
  • Abstract Understanding the mechanisms of gene regulation in the field of systems biology is a very important issue. With the development of bio-information technology, we can capture large quantities of gene’s expression data from DNA microarray data. In order to discover the relationship of gene regulation, the simulation of gene regulatory networks have been proposed. Among these simulations methods, the S-system model is the most widely used in non-linear differential equations. It can simulate the dynamic behavior of gene regulatory networks and gene expression, but can’t explain the structure and orientation of gene regulatory networks. Therefore, we propose a Boolean knowledge-based approach to assist the S-system modeling of gene regulatory networks.
    In this study, we derive the positive and negative regulatory relationships between genes from the regulation of S-system parameters, and use the structure of Boolean networks as our knowledge base. According to the results of the experiment, we can verify our assumptions for the regulation of the S-system parameters, and also has a better understanding of the regulatory relationship between genes.
    Advisory Committee
  • Yuh-Jiuan Tsay - chair
  • Chang, T. M - co-chair
  • W.-P. Lee - advisor
  • Bingchiang Jeng - advisor
  • Files
  • etd-0320112-103212.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2012-03-20

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