Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection.
BACKGROUND
The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge.


RESULTS
The main kinetics of the immune response were identified by fuzzy clustering of gene expression profiles (time series). The number of clusters was optimized using various evaluation criteria. For each cluster a representative gene with a high fuzzy-membership was chosen in accordance with available physiological knowledge. Then hypothetical network structures were identified by seeking systems of ordinary differential equations, whose simulated kinetics could fit the gene expression profiles of the cluster-representative genes. For the construction of hypothetical network structures singular value decomposition (SVD) based methods and a newly introduced heuristic Network Generation Method here were compared. It turned out that the proposed novel method could find sparser networks and gave better fits to the experimental data.


BACKGROUND
Reinhard.Guthke@hki-jena.de.
Guthke
Reinhard
R
Hans Knoell Institute for Natural Products Research, D-07745 Jena, Beutenbergstrasse 11a, Germany. Reinhard.Guthke@hki-jena.de
Möller
Ulrich
U
Hoffmann
Martin
M
Thies
Frank
F
Töpfer
Susanne
S
D000465:Algorithms; D003198:Computer Simulation; D016207:Cytokines / Q000276:immunology*; D004927:Escherichia coli Infections / Q000276:immunology*; D020869:Gene Expression Profiling / Q000379:methods*; D005786:Gene Expression Regulation / Q000276:immunology*; D006681:HLA-D Antigens / Q000276:immunology*; D006801:Humans; D018448:Models, Immunological; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D015398:Signal Transduction / Q000276:immunology*
D016207:Cytokines; D006681:HLA-D Antigens