An algorithmic framework for network reconstruction

by Durzinsky, M.; Wagler, A.; Weismantel, R.


Preprint series: 09-30, Preprints

The paper is published: Theoretical Computer Science

92B99 None of the above but in this section
68R05 Combinatorics


Abstract: Models of biological systems and phenomena are of high scientific interest and practical relevance, but not always easy to obtain due to their inherent complexity. To gain the required insight, experimental data are provided and need to be interpreted in terms of models that explain the observed phenomena. In systems biology the framework of Petri nets is often used to describe models for the regulatory mechanisms of biological systems. The aim of this paper is to provide an algorithmic framework for the challenging task of generating all possible Petri nets fitting the given experimental data.

Keywords: computational biology, reverse engineering, integer decomposition, Petri nets

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Letzte Änderung: 01.03.2018 - Ansprechpartner:

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