Digital Public Defence: Marius Gheorghe

MSc Marius Gheorghe at Centre for Molecular Medicine Norway will be defending the thesis Integrative approaches to study TF-DNA interactions for the degree of PhD (Philosophiae Doctor).

The University of Oslo is closed and the public defence will be held as a video conference over Zoom.

The defence will follow regular procedure as far as possible, hence it will be open to the public and the audience can ask ex auditorio questions when invited to do so.

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Digital trial lecture - time and place

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Adjudication committee

  • First opponent: Group Leader Judith Zaugg, European Molecular Biology Laboratory, Heidelberg, Germany  
  • Second opponent: Associate Professor Eivind Valen, University of Bergen 
  • Third member and chair of the evaluation committee: Group Leader Marieke Kuijjer, Centre for Molecular Medicine Norway, University of Oslo 

Chair of defence

Centre Director Janna Saarela, Centre for Molecular Medicine Norway, University of Oslo 

Principal Supervisor

Head of Group Anthony Mathelier, Centre for Molecular Medicine Norway, University of Oslo

Summary

Transcriptional regulation is a crucial process for cell differentiation and development. This process is tightly coordinated by the binding of key proteins, called transcription factors (TFs), to the DNA in a sequence-specific manner. The binding of TFs at their TF binding sites (TFBSs) ensures that the right genes are expressed in the right tissue and at the right levels. Alterations occurring at TFBSs, due to mutations or other genomic alterations, can disrupt the transcriptional regulatory mechanism, affecting entire gene regulatory networks, which in turn can lead to diseases such as cancer.

The aim of the thesis was to develop and improve computational tools and methodologies for genome-wide identification of TFBSs, capitalizing on the large amounts of publicly available ChIP-seq data (the most popular experimental assay capturing TF-DNA interactions in vivo), and use this information to infer gene regulatory networks.

Employing a non-parametric, entropy-based computational approach, we improved our capacity to identify bona fide TFBSs. As a result, a map of direct TF-DNA interactions in the human genome, hosting ~8 million binding sites for more than 230 TFs was generated and made publicly available. This resource, together with other relevant genomic information, served as a base for improving the prediction of TF target genes, called regulons, furthering the identification of gene regulatory networks. Altogether, these resources were put to use in a practical setting, identifying candidate TFs involved in breast cancer development, discriminating between estrogen receptor positive and negative breast cancer subtypes.

In brief, this thesis presents the development of new computational methods and resources that are derived from in depth analyses of experimentally-generated data to study gene expression regulation and how it can be disrupted in diseases such as cancer.

Additional information

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Published Apr. 30, 2020 12:59 PM - Last modified May 15, 2020 12:40 PM