5 July 2019
on course website
Integrative X-omics Analysis Empowering Personalized Healthcare
In this course you will receive high profile lectures and practical training on the integrated use of molecular-omics technologies in personalized prevention, diagnostics and treatment, to optimize your experimental and analysis strategies.
Molecular indicators for health, disease and response to treatment are increasingly guiding personalized healthcare. At the same time, single biomarkers will never fully reflect the interplay between the genetic make-up and environmental exposure. This asks for a more holistic view on human health, and integrated analyses of large-scale molecular and clinical data. This course will lay a firm basis for such an integrative approach. The course provides a comprehensive overview of state-of-the-art biomarker discovery strategies using -omics analysis platforms, gives practical cues to the most fit-for-purpose experimental approaches, based on real-life examples. The basic principles and workflows of genomics, transcriptomics, proteomics, and metabolomics experiments will be covered. The course will contain demonstrations and hands-on computer tutorials of commonly used open-source analysis and visualization packages. Special attention will be paid to the different ways to integrate X-omics data, ranging from pure statistical integration approaches (including machine learning) to knowledge-based data integration.
P.A.C. ’t Hoen
Professor of Bioinformatics
Centre for Molecular and Biomolecular Informatics
A.J. van Gool
Professor of Personalized Healthcare
Master, PhD and post-doc. This course is designed for translational researchers who would like to set-up or are starting a molecular biomarker profiling study in human individuals.
1.Design an X-omics experiment using the most adequate -omics technologies
2.Apply basic -omics analysis workflows
3.Discuss the advantages and disadvantages of different data integration strategies
EUR 550: Normal fee
€ 495 early bird discount – deadline 1 March 2019 (10%)
€ 468 partner + RU discount (15%)
€ 413 early bird + partner + RU discount (25%)
on course website