Developing models that can represent biochemical systems is one of the hallmarks of systems biology. Scientists have been gathering data from actual experiments, but there is a lack in computer models that can be used by scientists in analysing the various biochemical systems more effectively. In this research, we propose to use an ant colony optimization (ACO) algorithm for the network inferen...

In systems biology, a key topic is the elucidation of the dynamic behavior of biological processes that are made up of complex biochemical networks. Statistical modeling is an important to capture the dynamics of biochemical networks such as metabolic networks, signal transduction pathways, and gene regulatory networks. These biochemical models have a set of parameters that represent the physic...

The identification of suitable model parameters for biochemical reactions has been recognized as a quite difficult endeavor. Parameter values from literature or experiments can often not directly be combined in complex reaction systems. Nature-inspired optimization techniques can find appropriate sets of parameters that calibrate a model to experimentally obtained time series data. We present S...