Chapter Category: Bioinformatics

From the book Discovering Biomolecular Mechanisms with Computational Biology

The Predictive Power of Molecular Network Modelling: Case Studies of Predictions with Subsequent Experimental Verification

Stefan Schuster*, Edda Klipp and Marko Marhl

Since the 1960s, the mathematical modelling of intracellular systems, such as metabolic pathways, signal transduction cascades and transport processes, is an ever-increasing field of research. The results of most modelling studies in this field are in good qualitative or even quantitative agreement with experimental results. However, a widely held view among many experimentalists is that modelling and simulation only reproduce what has been known before from experiment. A true justification of theoretical biology would arise if theoreticians could predict something unknown, which would later be found experimentally. Theoretical physics has achieved this justification by making many right predictions, for example, on the existence of positrons. Here, we review three cases where experimental groups that were independent of the theoreticians who had made the predictions confirmed theoretical predictions on features of intracellular biological systems later. The three cases concern the optimal time course of gene expression in metabolic pathways, the operation of a metabolic route involving part of the tricarboxylic acid cycle and glyoxylate shunt, and the decoding of calcium oscillations by calcium-dependent protein kinases.

Taken from the book

Discovering Biomolecular Mechanisms with Computational Biology

Edited by: Stefan Schuster*, Edda Klipp and Marko Marhl

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