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.
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Blöchl, F., Theis, F.J. (2009). Estimating Hidden Influences in Metabolic and Gene Regulatory Networks. In: Adali, T., Jutten, C., Romano, J.M.T., Barros, A.K. (eds) Independent Component Analysis and Signal Separation. ICA 2009. Lecture Notes in Computer Science, vol 5441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00599-2_49
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DOI: https://doi.org/10.1007/978-3-642-00599-2_49
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