MoKa - Molecular Karyotyping
From 01-10-2007 to 30-09-2011
Description
This research proposal aims to push the technical limits of Array CGH. By advancing the potential of molecular karyotyping, both by improving technology and data analysis methods, we will create novel applications in research as well as novel possibilities for genetic diagnosis. First, we will develop genomewide analysis of genomic imbalances from a single cell. This will allow us to answer long standing questions about early embryogenesis and tumor development. Second, we will push back the limits of the technology to detect low-grade mosaicisms, which are genetic imbalances in only a fraction of a mixture of cells. This in turn will allow us to investigate fetal DNA in the maternal plasma as well as improved analysis of tumors, lymphomas, and leukemias and probing potentially undetected causes of recurrent miscarriages and subfertility. Third, we will investigate the role of epigenetic phenomena in X-linked chromosomal anomalies, constitutional anomalies, and cancer. Finally, we will maximize the effectiveness of these advances in array CGH by developing novel data-interpretation methods. Statistical approaches, data storage and vizualisation tools developed in each of these domains wil cross-fertilize the advances in the other domains.These advances will not only enable to answer new basic questions, but change human genetic diagnosis. Single cell array CGH analysis will improve preimplantation genetic diagnosis and possibly the diagnosis of certain types of tumors. Mosaicism detection will influence and change the fields of prenatal and postnatal diagnosis of constitutional and acquired disorders. It is well known that epigenetic processes play an important role in both constitutional and acquired diseases. The potential of arrays to get a genomewide overview of epigenetic changes might be tremendous. In particular, for the diagnosis of several types of cancers, the lack of a genomewide screening tool has been limiting the diagnostic potential. Finally, we foresee that the huge amount of novel (biological) information coming from these analyses will require bioinformatics approaches to aid clinicians and laboratory directors in decision making and help researchers in understanding their findings. Since each application might use the different proposed technological fields, data storage, visualization and analysis tools will be shared among applications.
Team
- Yves Moreau, Co-promoter
- Joris Vermeesch, Promoter (External)
- Bert Coessens, Team member
- Steven Van Vooren, Team member
Financing
Funding: IWT - Agentschap voor Innovatie door Wetenschap en Technologie
Program/Grant Type: IWT SBO - IWT Projects Strategic Basic Research
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.