• Posttranscriptional regulatory networks in neurodegenerative diseases
The Client : Javna agencija za raziskovalno dejavnost RS
Project type: Research projects ARRS
Project duration: 2013 - 2016
  • Description
Recent years have seen intensive developments of new methods for understanding the function of RNA-binding proteins or RBPs, which are based on high-throughput sequencing (HTS). These data require new computational tools. In this project, we plan to develop tools that will considerably contribute to the understanding of the principles of gene expression regulation on the RNA level and thus accelerate research in the field of bioinformatics. We will develop new artificial intelligence tools and integrate them in the”iDiscover” intelligent web assistant to analyze HTS data. The tools will significantly speed up the otherwise computationally intensive studies of interactions between proteins and RNA, and the role of proteins in gene expression. It is essential that the tools are also able to set new hypotheses, which will serve as starting points for new experiments in Ule's research group. The aim of this group is to understand the regulatory mechanisms of gene expression that contribute to neurodegenerative diseases. Specifically, we would like to achieve the following objectives: 1) Develop and implement a computational pipeline for mapping readings, quantification and visualisation of protein-RNA interactions, and the modelling of gene expression regulation. 2) Develop a new descriptive language and efficient heuristics for the integration and modelling of relations between different stages of post-transcriptional regulation. Automatically generate new hypotheses that explain the molecular functions of proteins which bind RNA. 3) Construct predictive models using machine learning and implement ”iDiscover”, the intelligent web interface, which will lead researchers in discovering regulatory mechanisms of individual RBPs. 4) Integrate data from HTS methods for understanding molecular mechanisms of two proteins, which are associated with neurodegenerative diseases: TD-43 and FUS. Zupan's group (FRI), University of Ljubljana, Faculty of Computer and Information Science, Ljubljana, Slovenia, has extensive experience and knowledge of analysis and visualisation of HTS data, machine learning and software development. Members of Zupan's group will collaborate closely with members of Ule's group (LMB), MRC Laboratory of Molecular Biology, Cambridge, UK, who develop new experimental methods and have specialist knowledge in the field of genomics and the study of protein-RNA interaction. Both groups with cooperate with Rogelj's group (JSI), Jožef Stefan Institute, Ljubljana, Slovenia, with expertise in the field of neurobiology and the study of signalling pathways that regulate a variety of RBPs. All three groups have successfully participated in the past and jointly achieved important results and publications, which guarantees the success of this project as well.