Recent experiments have revealed unexpected plasticity and dynamic nature of the human proteome. The paradigm that the time evolution of a biological system can be described by abundance variation of relatively few “regulated” proteins has been shuttered. Instead, understanding is growing that the whole proteome is regulated, and no protein remains unaffected when the system undergoes transition from one state to another.
This finding underlines the importance of systems biology analysis of expression proteomics data. Systems biology shifts the analytical focus from thousands of proteins to hundreds of signaling pathways, thus reducing the number of entities to be analyzed. Application of these methods required the development of novel systems biology tools, such as the pathway search engine. These tools can only be effective when they are quantitative, i.e. predict not only the activated pathway, but also the relative degree of its activation. Introducing the quantitative aspect in systems biology is one of the greatest challenges this field is facing today, since the final goal of pathway analysis, which is the creation of a quantitative predicting model of the biological process under investigation.
Yet pathway analysis is not the only method of complexity reduction. Two more, complementary approaches will be discussed: correlation analysis and mapping on amino acid and elemental compositions.
