With the rising application of systems biology, sensitivity analysis methods have been widely
applied to study the biological systems, including metabolic networks, signalling pathways …

Due to the wide use and key importance of mathematical models in process engineering,
experiment design is becoming an essential tool for the rapid building and validation of …

Motivation: Over the last decade, numerous methods have been developed for inference of
regulatory networks from gene expression data. However, accurate and systematic …

The advent of functional genomics has enabled the molecular biosciences to come a long
way towards characterizing the molecular constituents of life. Yet, the challenge for biology …

Availability of large-scale experimental data for cell biology is enabling computational
methods to systematically model the behaviour of cellular networks. This review surveys the …

Background Systems biology has embraced computational modeling in response to the
quantitative nature and increasing scale of contemporary data sets. The onslaught of data is …

Reverse engineering methods are typically first tested on simulated data from in silico
networks, for systematic and efficient performance assessment, before an application to real …

Background We consider the problem of parameter estimation (model calibration) in
nonlinear dynamic models of biological systems. Due to the frequent ill-conditioning and …

The interplay of mathematical modelling with experiments is one of the central elements in
systems biology. The aim of reverse engineering is to infer, analyse and understand …

Experimental design has a long tradition in statistics, engineering and life sciences, dating
back to the beginning of the last century when optimal designs for industrial and agricultural …