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1.1. Databases for
new data types.
Responsible:
Jürgen Eils, DKFZ,
Heidelberg.
Background:
This sub-project is dedicated
to the enhancement of the highly successful
iCHIP database.
The database is installed at several clinical labs within the "CancerNet", "NeuroNet" and "Infection/InflammationNet",
and the number of installations continues to grow.
iCHIP abides by MIAME- and MAGE-standards (minimum
information about a microarray experiment and
microarray and gene expression markup language,
respectively) of the international MGED (microarray
gene expression databases) consortium. Although
iCHIP was initially developed as a local
decentralized data storage solution for microarray
data from both oligonucleotide and cDNA chips (funded
by the optimization fund of NGFN1) we aim to extend
the remit of the system during the course of this
project. Because of its flexible and modular
construction, iCHIP is easily extensible, a factor
we will capitalize upon during the implementation
phase.
Planned work:
As
the data deluge continues unabated, so too does the
diversity of data types it contains. Requisite to
the transformation of these data into meaningful
knowledge is the need for intelligent, standardized
and extensible data management solutions. In this
subproject, we aim to utilise the iCHIP framework
for the integration and association of pertinent
biological data types; primarily derived from
proteomics, matrix-CGH, tissue microarrays (TMA) and
cellular assays in combination with RNAi technology.
We will integrate these data through the development
of both a uniform mask design and novel methods for
querying the comprehensive heterogeneous dataset in
a meaningful manner. The integration of high-quality
data standards and well-defined requirements lists
from molecular biologists will be key determining
factors in the success of this project.
Publications:
Eils J and Lawerenz C. Database concepts for system biology.
Computational systems biology. (Book; Elsevier).
Schramm A, Schulte JH, Klein-Hitpass L, Havers W, Sieverts H,
Berwanger B, Christiansen H, Warnat P, Brors B, Eils J, Eils R,
Eggert A. Prediction of clinical outcome and biological
characterization of neuroblastoma by expression profiling.
Oncogene. 2005 Nov 24;24(53):7902-7912.
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