最小二乗法に基づくタンパク質ネットワークの推定とロバストネス解析

抄録

This paper considers an estimation problem of protein networks for phenomena in cell. By assuming that protein concentrations concerning the phenomena are obtained, an approach to solve the estimation problem is proposed. The proposed approach is based on the least-squares method for state space models. A 6-dimensional protein network is estimated for cell cycle in budding yeast to demonstrate the efficacy of the proposed approach. Moreover robustness analysis and numerical simulations are performed by deriving nonlinear equations which describe a dynamical behavior of the estimated protein network. From these theoretical and numerical results, robustness of the estimated protein network is discussed.