Estimating Hidden Influences in Metabolic and Gene Regulatory Networks

Authors:
Florian Blöchl;Fabian J. Theis
Affiliations:
Institute for Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany 85764;Institute for Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany 85764 and Max-Planck-Institute for Dynamics and Self-Organization, Göttingen, Germany
Venue:
ICA '09 Proceedings of the 8th International Conference on Independent Component Analysis and Signal Separation
Year:
2009

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Abstract

We address the applicability of blind source separation (BSS) methods for the estimation of hidden influences in biological dynamic systems such as metabolic or gene regulatory networks. In simple processes obeying mass action kinetics, we find the emergence of linear mixture models. More complex situations as well as hidden influences in regulatory systems with sigmoidal input functions however lead to new classes of BSS problems.