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SyMbolic

Systemic Models for Metabolic Dynamics and Regulation of Gene Expression

As a result of the rapidly developed measurement technologies an increasing amount of biological data has become available. For example microarray measurements provide an easy way to investigate activity of all the genes in an organism. However, even a "simple" biological cell contains such a complex network of chemical reactions and gene interactions that reductionistic approaches cannot be used to analyse the complete system. That is why novel data-based approaches and special knowledge of deeper systems theory are becoming increasingly important issues also in biology.

Our goal in this project is to combine the understanding of traditional systems modeling and control theory with biological data. This way we hopefully can provide new approaches to diminish the gap between the still quite separate fields of cell biology and systems engineering. The focus is especially on the data-based dynamic modeling of complex systems with high number of variables and plenty of internal connections; that is, we are considering biological cells as cybernetic systems.

This project is a part of the Tekes NeoBio program. Our partners are Medicel Ltd., Laboratory of Computer and Information Science, TKK and CSC - Finnish IT center for science. Our research is financed by Tekes.

  • Keywords: bioinformatics, systems biology, gene expression, data-based modeling, dynamic modeling, latent variable models
  • Duration: 2004-2005
  • Research area: Cybernetics
  • Publications (total: 3)

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Master's Theses