Metabolome has become an important part of Systems Biology, and a large set of data has already gained by applying the methods of metabolome. How to deal with the data and how to combine data of metabolome with data of other omics are problems that can not be ignored. An Enzyme Amount Multiple Factor was imported into the enzyme kinetic equation. When the enzyme amount in the system changed, in silico model, it means to alter the Enzyme Amount Multiple Factor. In order to observe ethanol concentration response to enzyme amount changes in S. cerevisiae glycolysis pathway model, enzyme amount was separately set at high and low level, the corresponding Enzyme Amount Multiple Factor value was 10 and 0.1, relatively. Based on the result of simulation, twelve enzymes in pathway were separated into two classes, class I and class II by cluster analysis. The four enzymes belonging to class I, ADH, HK, PFK and PDC, all catalyze irreversible reactions. The six out of eight enzymes belonging to class II, ALD, GAPDH, GlcTrans, lpPEP, PGI and TIM, catalyze reversible reactions. The other two enzymes belonging to class II, lpGlyc and PK, catalyze irreversible reactions. Based on this method, data of metabolome and proteomics are easily integrated to accomplish relatively overall analysis of system properties.
|Evidence ID||Analyze ID||Interactor||Interactor Systematic Name||Interactor||Interactor Systematic Name||Type||Assay||Annotation||Action||Modification||Phenotype||Source||Reference||Note|
|Evidence ID||Analyze ID||Gene||Gene Systematic Name||Gene Ontology Term||Gene Ontology Term ID||Qualifier||Aspect||Method||Evidence||Source||Assigned On||Annotation Extension||Reference|
|Evidence ID||Analyze ID||Gene||Gene Systematic Name||Phenotype||Experiment Type||Experiment Type Category||Mutant Information||Strain Background||Chemical||Details||Reference|
|Evidence ID||Analyze ID||Regulator||Regulator Systematic Name||Target||Target Systematic Name||Experiment||Assay||Construct||Conditions||Strain Background||Reference|