Modeling of gene expression

Our aim is to construct models of gene regulatory networks by analyzing and integrating signals from various experiments.
GeneRegulation (20K)
GeneRegulation (20K) I. Gene regulation: Gene expression is a multi-step process where the information coded within a gene is transformed into a protein. Since diverse sets of proteins are necessary under different conditions the expression of genes is under tight regulation.
The expression of many genes is regulated by transcription factors (TF). TF's are proteins that bind to a specific DNA sequence and recruit or repress the transcriptional machinery. TF's are themselves controlled at the level of transcription and/or through other types of signals, i.e. signal transduction.
GeneRegulation (20K)
GeneRegulation (20K) II. Data sources: An increasing amount of transcriptional data is being collected, providing valuable insight to cellular processes under various conditions. Today, modeling is guided by a rich flow of experimental data. The stream is still widened by an increasing pool of measurement techniques including mRNA microarray technology (mRNA Chips), chromatin immunoprecipitation (TF-DNA binding) and sequence based methods (motif search).
GeneRegulation (20K)
GeneRegulation (20K) III. Computational approaches: The interpretation of biological data calls for abstract representations of biochemical entities. To model these biochemical entities different analytical or statistical methods can be employed. In our modeling approach we try to capture gene regulation on a detailed level. Such detailed models are then used as groundwork to build global models of gene expression. Finally, it is our goal to infer gene regulatory networks from measurements of the expression state of a cell, thus to reverse engineer GRN's.
GeneRegulation (20K)

Funding

NGFN_Logo (10K)

References

Reverse Engineering Non-Linear Gene Regulatory Networks Based on the Bacteriophage λ cI Circuit
Jochen Supper, Christian Spieth and Andreas Zell
accepted at the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) 2005, San Diego, USA
Feedback Memetic Algorithms for Modeling Gene Regulatory Networks
C. Spieth, F. Streichert, J. Supper, N. Speer, and A. Zell
accepted at the 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB) 2005, San Diego, USA

Contact

Jochen Supper, Tel.: (07071) 29-77176, supper at informatik.uni-tuebingen.de