Estimating hidden influences in metabolic and gene regulatory networks

Florian Blöchl, Fabian J. Theis

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


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.

Original languageEnglish
Pages (from-to)387-394
Number of pages8
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
StatePublished - 2009
Externally publishedYes
Event8th International Conference on Independent Component Analysis and Signal Separation, ICA 2009 - Paraty, Brazil
Duration: 15 Mar 200918 Mar 2009


Dive into the research topics of 'Estimating hidden influences in metabolic and gene regulatory networks'. Together they form a unique fingerprint.

Cite this