Call for papers: Special issue on systems identification for biological systems

Experimental techniques in molecular biology have led to the production of enormous amounts of data on the
dynamics of cellular processes. The availability of time series data characterizing genomic, proteomic and metabolic
systems must be complemented with formal methods for identifying quantitative models of networks of interactions.
Reverse-engineering of regulatory networks is a central issue in modern biology because, beside enabling the
computer-based simulation of biological systems, it promotes the understanding of cell functioning and underlies
the design of interventions of biotechnological or biomedical relevance. However, standard system identification
techniques are unlikely to work out of the box since they must cope with (1) the complexity and the high nonlinearity
of biological systems; (2) the quality and type of available biological data; (3) the stochastic nature of chemical
interactions; and (4) the interaction of discrete events and continuous dynamics.
The aim of this special issue is to present some very recent achievements in system identification tailored to the
reconstruction of biological processes.