Gene expression analysis on biochemical networks using the Potts spin model.
BACKGROUND
Microarray technology allows us to profile the expression of a large subset or all genes of a cell. Biochemical research over the last three decades has elucidated an increasingly complete image of the metabolic architecture. For less complex organisms, such as Escherichia coli, the biochemical network has been described in much detail. Here, we investigate the clustering of such networks by applying gene expression data that define edge lengths in the network.


RESULTS
The Potts spin model is used as a nearest neighbour based clustering algorithm to discover fragmentation of the network in mutants or in biological samples when treated with drugs. As an example, we tested our method with gene expression data from E.coli treated with tryptophan excess, starvation and trpyptophan repressor mutants. We observed fragmentation of the tryptophan biosynthesis pathway, which corresponds well to the commonly known regulatory response of the cells.
König
Rainer
R
Division Intelligent Bioinformatics Systems, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. r.koenig@dkfz.de
Eils
Roland
R
D000465:Algorithms; D016000:Cluster Analysis; D003198:Computer Simulation; D004734:Energy Metabolism / Q000502:physiology; D004926:Escherichia coli / Q000378:metabolism*; D020869:Gene Expression Profiling / Q000379:methods*; D015964:Gene Expression Regulation, Bacterial / Q000502:physiology; D008954:Models, Biological; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D015398:Signal Transduction / Q000502:physiology*; D012984:Software; D014364:Tryptophan / Q000235:genetics / Q000378:metabolism*
D014364:Tryptophan