TY  - GEN
A1  - Szymanski, Jedrzej
A1  - Jozefczuk, Szymon
A1  - Nikoloski, Zoran
A1  - Selbig, Joachim
A1  - Nikiforova, Victoria
A1  - Catchpole, Gareth
A1  - Willmitzer, Lothar
T1  - Stability of metabolic correlations under changing environmental conditions in Escherichia coli : a systems approach
N2  - Background: Biological systems adapt to changing environments by reorganizing their cellula r and physiological program with metabolites representing one important response level. Different stresses lead to both conserved and specific responses on the metabolite level which should be reflected in the underl ying metabolic network. Methodology/Principal Findings: Starting from experimental data obtained by a GC-MS based high-throughput metabolic profiling technology we here develop an approach that: (1) extracts network representations from metabolic conditiondependent data by using pairwise correlations, (2) determines the sets of stable and condition-dependent correlations based on a combination of statistical significance and homogeneity tests, and (3) can identify metabolites related to the stress response, which goes beyond simple ob servation s about the changes of metabolic concentrations. The approach was tested with Escherichia colias a model organism observed under four different environmental stress conditions (cold stress, heat stress, oxidative stress, lactose diau xie) and control unperturbed conditions. By constructing the stable network component, which displays a scale free topology and small-world characteristics, we demonstrated that: (1) metabolite hubs in this reconstructed correlation networks are significantly enriched for those contained in biochemical networks such as EcoCyc, (2) particular components of the stable network are enriched for functionally related biochemical path ways, and (3) ind ependently of the response scale, based on their importance in the reorganization of the cor relation network a set of metabolites can be identified which represent hypothetical candidates for adjusting to a stress-specific response. Conclusions/Significance: Network-based tools allowed the identification of stress-dependent and general metabolic correlation networks. This correlation-network-ba sed approach does not rely on major changes in concentration to identify metabolites important for st ress adaptation, but rather on the changes in network properties with respect to metabolites. This should represent a useful complementary technique in addition to more classical approaches.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - paper 147 
KW  - Small-world networks
KW  - saccharomyces-cerevisiae
KW  - trehalose synthesis
KW  - gene-expression
KW  - stress-response
Y1  - 2009
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-45253
ER  - 
TY  - GEN
A1  - Dworschak, Steve
A1  - Grell, Susanne
A1  - Nikiforova, Victoria J.
A1  - Schaub, Torsten H.
A1  - Selbig, Joachim
T1  - Modeling biological networks by action languages via answer set programming
T2  - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe
N2  - We describe an approach to modeling biological networks by action languages via answer set programming. To this end, we propose an action language for modeling biological networks, building on previous work by Baral et al. We introduce its syntax and semantics along with a translation into answer set programming, an efficient Boolean Constraint Programming Paradigm. Finally, we describe one of its applications, namely, the sulfur starvation response-pathway of the model plant Arabidopsis thaliana and sketch the functionality of our system and its usage.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 843 
KW  - biological network model
KW  - action language
KW  - answer set programming
Y1  - 2020
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-429846
SN  - 1866-8372
IS  - 843
ER  - 
TY  - THES
A1  - Nikiforova, Victoria
T1  - Processing of metabolic information through biological networks
Y1  - 2010
CY  - Potsdam
ER  -