Classification of proteomic kinetic patterns using supervised genetic programming

The rapidly emerging field of quantitative proteomics has established itself as a credible approach for understanding of the biology of whole organisms. Classification of proteins according to the level of their expression during a particular process allows discovering causal relationships among genes and proteins involved in the process. In the paper we present a supervised method of classification of proteomic kinetic patterns based on genetic programming allowing for extraction of user defined patterns from a database of kinetic profiles. The method combines robustness of genetic programming algorithm with the flexibility given by user interaction.