DA 1.0: Parameter estimation of biological pathways using data assimilation approach

Abstract

Summary: Data assimilation (DA) is a computational approach that estimates unknown parameters in a pathway model using time-course information. Particle filtering, the underlying method used, is a well-established statistical method that approximates the joint posterior distributions of parameters by using sequentially generated Monte Carlo samples. In this article, we report the release of Java-based software (DA 1.0) with an intuitive and user-friendly interface to allow users to carry out parameters estimation using DA. © The Author 2010.