Abstract

Biochemical pathways are typically thought as complex networks of chemical compounds and reaction in the living organisms. A great amount of gene expression data that have a bearing on pathway is created at an increasing rate by microarray technology. The large ensemble of information that the gene expression experiments produce contains pattern that are a reflection of pathway dynamic, and therefore can be used to deduce pathway causal structure. Conceptual data modelling involves the development of implementation-independent models that capture and make explicit the principal structural properties of the data. This thesis develops and presents such a data modeling for biochemical pathway and microarray gene expression. The conceptual data models can be transformed in systematic ways for implementation using different platforms, e.g. traditional database management system and visualisation pathway application. This conceptual data model is described by widely used conceptual modelling notation: the class diagrams of UML (unified modelling language).