Genetic Network Inference - Development of a generic methodology for genetic network inference
From 10-01-2001 to 30-09-2006
Description
Bioinformatics research has focused mainly on the application of mathematical methods on high-dimensional data generated by high-throughput molecular and biological techniques. Part of those tools lack the necessary biological relevance. The future of bioinformatics lies in the design of more biology oriented algorithms. This interdiscplinary research project can be situated in this perspective. Concretely, the selection, implementation and optimization of existing mathematical methods for the identification and modeling of regulatory interactions is studied. Thanks to the accomplishments in high-throughput screening it is now possible to measure simultaneously the expression level of a large set of genes. This flood of data has to be processed with the right datamining and modeling techniques. Genetic network inference is a great challenge both from a biological and systems identification viewpoint. The development of a mathematical framework for inference implies robust preprocessing, optimized feature extraction, selection of the most appropriate model class and training procedure, and interpretation of the results. SCD will profit from the finetuning and optimization of existing methods. From a biological point of view, genetic network inference forms the basis of fundamental and applied research. Since we like to develop a generic method to model regulatory networks in procaryotes and eucaryotes, we opt to study the glycolyzation pathway in yeast and the Type III secretion system (TTSS) in Salmonella thypimurium.Team
- Kathleen Marchal, Coordinator
- Bart De Moor, Promoter
Financing
Funding: KU Leuven - Internal Funding KU Leuven
Program/Grant Type: BOF-Research - BOF Research Programmes
Events
2/09/2024:
PhD defense - Martijn Oldenhof
Machine Learning for Advanced Chemical Analysis and Structure Recognition in Drug Discovery
3/09/2024:
Meet the Jury Igor Tetko on Advanced Machine Learning in Drug Discovery
12/09/2024:
Multimodal analysis of cell-free DNA for sensitive cancer detection in low-coverage and low-sample settings
Seminar by Antoine Passemiers
News
STADIUS Alumni Herman Verrelst – new CEO of Biocartis
08 June 2017
Herman Verrelst, the founder of KU Leuven spin-off Cartagenia, who has been working in Silicon Valley, US for the last few years will be returning to Belgium to follow the steps of Rudi Pauwels as CEO of the Belgian diagnostic company, Biocartis.
Supporting healthcare policymaking via machine learning – batteries included!
29 May 2017
STADIUS takes the lead in the data analytics efforts in an ambitious European Project MIDAS.
Marc Claesen gives an interview about his PhD for the magazine of the Faculty of Engineering Sciences "Geniaal"
10 February 2017
Did you know that in Belgium approximately one third of type 2 diabetes patients are unaware of their condition?
Joos Vandewalle is nieuwe voorzitter KVAB
09 October 2016
Op 5 oktober 2016 heeft de Algemene Vergadering van de Academie KVAB Joos Vandewalle verkozen tot voorzitter van de KVAB.