Genomic Data Explosion - The Challenge for Bioinformatics?

Authors:
Änne Glass;Thomas Karopka
Affiliations:
-;-
Venue:
Industrial Conference on Data Mining: Advances in Data Mining, Applications in E-Commerce, Medicine, and Knowledge Management
Year:
2002

Citing 6
Cited 0

A massively parallel architecture for a self-organizing neural pattern recognition machine

Computer Vision, Graphics, and Image Processing
Case-based reasoning: foundational issues, methodological variations, and system approaches

AI Communications
Data Mining Techniques: For Marketing, Sales, and Customer Support

Data Mining Techniques: For Marketing, Sales, and Customer Support
CBR in Medicine

Case-Based Reasoning Technology, From Foundations to Applications
Classificaiton of HEp-2 Cells Using Fluorescent Image Analysis and Data Mining

ISMDA '01 Proceedings of the Second International Symposium on Medical Data Analysis
Case-based reasoning for antibiotics therapy advice: an investigation of retrieval algorithms and prototypes

Artificial Intelligence in Medicine

Quantified Score

Hi-index	0.01

Visualization

Abstract

A dramatic increase in the amount of genomic expression data with knowledge in to mine for getting a principal understanding of "what is a considered disease at the genomic level" is available today. We give a short overview about common processing of micro array expression data. Furthermore we introduce a complex bioinformatic approach1 combining properly several analyzing methods to mine gene expression data and biomedical literature. Gene patterns and gene relation information as results from data and text mining is to be considered as integral part for modeling genetic networks. We apply methods of case-based-reasoning for generating a similarity tree consisting of genetic networks. These networks are efficient facilities to understand the dynamic of pathogenic processes and to answer a question like "what is a disease x in the genomic sense"?