Objectives

• unraveling the holistic picture of the complex molecular interactions that occur on different molecular levels (genomic, transcriptomic, epigenomic, proteomic, etc). Therefore, the need to integrate/jointly analyzes biological data from different high-throughput technologies has been emerged in order to identify biomarkers for early diagnosis and prognosis of complex diseases and facilitating the development of novel treatment approaches.

Outcomes

This course aims at teaching students how to perform data-specific computational analysis as well as integrative analysis approaches, combining knowledge from different OMICs-based datasets using network-based approaches and basics of machine learning methods.

Course Contents

Both, theoretical and practical aspects will be covered. Students will have the opportunity to work both independently during tutorials and in teams during the research project. Students will be developing their own research projects, interpreting the obtained results, and critically defending their computational approaches while presenting.

Description

Data will be available soon!