Genomic Data Explosion – The Challenge for Bioinformatics? - Advances in Data Mining - page 80

Genomic Data Explosion - The Challenge for
Bioinformatics?

Änne Glass and Thomas Karopka

University of Rostock, Institute for Medical Informatics and Biometry,
Rembrandt-Str. 16/17, 18055 Rostock, Germany
{aenne.glass,thomas.karopka}@medizin.uni-rostock.de
http://www.med.uni-rostock.de

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 approach 1 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”?

1 Introduction

A dramatic increase in the amount of electronic stored information has been seen in
recent years. It has been estimated that the amount of information in the world
doubles every 20 month. These new data promise to enhance fundamental
understanding of life on the molecular level [1] . The advent of new technologies has
empowered genome researchers to measure the concentrations of every transcript in
the cell in a single experiment. It has added new dimensions to our ability to
leverage information from genome sequencing projects into a more comprehensive
and holistic understanding of cell physiology. The scientific community has not
determined how to cope with the massive amounts of data explored and interpreted
in the context of other sources of biological and medical knowledge. For example,
at Stanford and Rosetta alone, more than 30 million independent gene expression
measurements (one gene, one condition) have been made between 1997 and 1999
[2] . The way we do biology changes towards a more holistic view of biological
systems which is significantly different from the classical idea of investigating one
or a few genes at a time.

1

Funded by German Ministry for Education and Research (Bundesministerium für Bildung
und Forschung, BMBF); Grant Number: FKZ 01GG9831