- Communication -
| In Silico Biology 2, 0019 (2002); ©2002, Bioinformation Systems e.V. |
A system architecture for genomic data analysis
Änne Glass and Lothar Gierl
University of Rostock, Faculty of Medicine, Institute for Medical Informatics and Biometry
Rembrandt-Str. 16 / 17, D – 18055 Rostock
Email: aenne.glass@medizin.uni-rostock.de
Edited by E. Wingender; received December 13, 2001; revised and accepted January 31, 2002; published March 12, 2002
Abstract
Most of diseases are caused by a set of gene defects, which occur in a complex association. The association scheme of expressed genes can be modelled by genetic networks. Genetic networks are efficiently facilities to understand the dynamic of pathogenic processes by modelling molecular reality of cell conditions. In this sense a genetic network consists of first, a set of genes of specified cells, tissues or species and second, causal relations between these genes determining the functional condition of the biological system, i. e. under disease. A relation between two genes will exist if they both are directly or indirectly associated with disease [Oliver, 2000]. Our goal is to characterize diseases (especially autoimmune diseases like chronic pancreatitis CP, multiple sclerosis MS, rheumatoid arthritis RA) by genetic networks generated by a computer system. We want to introduce this practice as a bioinformatic approach for finding targets.
Keywords: genetic networks, model, functional genomics, proteomics, genomic data, expression data, chip data, data mining, analysis, bioinformatics, software system, complex association, causal relation, interaction, targets, artificial intelligence, AI, ART, parser engine