Title :
Classification of proteomic kinetic patterns using supervised genetic programming
Author :
To, Cuong ; Vohradsky, Jiri
Author_Institution :
Lab. of Bioinformatics, Microbiol. Inst., Czech Republic
Abstract :
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.
Keywords :
biology computing; genetic algorithms; pattern classification; proteins; scientific information systems; biology; causal relationships; kinetic profiles; pattern extraction; proteins; proteomic kinetic pattern classification; quantitative proteomics; supervised genetic programming; Databases; Gene expression; Genetic algorithms; Genetic programming; Kinetic theory; Organisms; Particle measurements; Proteins; Proteomics; RNA;
Conference_Titel :
Evolutionary Computation, 2005. The 2005 IEEE Congress on
Print_ISBN :
0-7803-9363-5
DOI :
10.1109/CEC.2005.1554909