Email updates

Keep up to date with the latest news and content from BMC Bioinformatics and BioMed Central.

Open Access Methodology article

Estimate hidden dynamic profiles of siRNA effect on apoptosis

Takanori Ueda1, Daisuke Tominaga2*, Noriko Araki1 and Tomohiro Yoshikawa1

Author affiliations

1 CytoPathfinder, Inc., 2-4-7 Aomi, Koto, Tokyo 135-0064, Japan

2 Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto, Tokyo 135-0064, Japan

For all author emails, please log on.

Citation and License

BMC Bioinformatics 2013, 14:97  doi:10.1186/1471-2105-14-97

Published: 15 March 2013



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.


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.


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’.

siRNA; RNA interference; Prey–predator model; Ordinary differential equation; Parameter estimation; Genetic algorithm