Estimate hidden dynamic profiles of siRNA effect on apoptosis

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• 作者：Takanori Ueda (8)
  Daisuke Tominaga (9)
  Noriko Araki (8)
  Tomohiro Yoshikawa (8)
  
• 关键词：siRNA ; RNA interference ; Prey–predator model ; Ordinary differential equation ; Parameter estimation ; Genetic algorithm
• 刊名：BMC Bioinformatics
• 出版年：2013
• 出版时间：December 2013
• 年：2013
• 卷：14
• 期：1
• 全文大小：208KB
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• 作者单位：Takanori Ueda (8)
  Daisuke Tominaga (9)
  Noriko Araki (8)
  Tomohiro Yoshikawa (8)
  
  8. CytoPathfinder, Inc., 2-4-7 Aomi, Koto, Tokyo, 135-0064, Japan
  9. Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto, Tokyo, 135-0064, Japan
  
• ISSN：1471-2105

文摘

Background For the representation of RNA interference (RNAi) dynamics, several mathematical models based on systems of ordinary differential equations (ODEs) have been proposed. These models consist of equations for each molecule that are involved in RNAi phenomena. Therefore, many real-value parameters must be optimized to identify the models. They also have many ‘hidden variables- which cannot be observed directly through experimentation. Calculation of the values of the hidden variables is generally very difficult, if not impossible in some special cases. Identification of the ODE models is also quite difficult. Results We show that the simplified logistic Lotka–Volterra model, a well-established ODE model for biological and biochemical phenomena, can represent RNAi dynamics as a predator–prey system. Although a hidden variable exists in the model, its values can be determined and made visible as dynamic profiles of RNA-decomposing effects of siRNAs. Correlation analysis shows that the model parameters correlate highly with the total effect of the siRNA. Conclusions The results suggest that analyses using our model are useful to estimate dynamic profiles of siRNA effects on apoptosis and to score siRNA by its effects on apoptosis, namely ‘phenotypic scoring-