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Omics Technologies and Data Analysis in Drug Discovery



OMICS: Omics technologies and data analysis in drug discovery

The course aims to provide an overview of the ‘omics’ technologies: state-of-the-art methods that can be used to analyze all genes, their transcripts, proteins and metabolites within a sample and difference between samples. Omics technologies are rapidly developing and have become nowadays indispensable in the research lab. The course will introduce students to genomic, transcriptomic, proteomic and metabolomic techniques, and the analytical approaches that can be employed to examine the data output from these approaches. Of note, in the context of functional genomics some particular attention will be drawn to the new gene editing technology (CRISPR/Cas 9 technology) that is revolutionizing research in biology. The course is not only an introduction to the omics technologies but also to the methods used for analysis of omics output data. The omics data analysis workflow will be introduced: from quantitative data to biological information (emphasis on analysis of transcriptomics). The following concepts will be addressed during the course: clinical experimental design and sample selection, introduction to data transformation and normalization, introduction to basic statistics in omics data analysis (significance test/p-values/false discovery rate), introduction to Gene Ontology and enrichment analysis, introduction to network and pathway analysis. Examples of the application of omic approaches in a variety of relevant biological systems will be presented, to give students an appreciation of the type of output generated.

Course Objectives

After completing the course, the student will be able:

  • to explain the different “omics” technologies that are currently applied to perform global analyses at a system level. Student will be able to compare state-of-the-art omics technologies including RNA-seq, smallRNA-seq, ChIP-seq, DNase-seq, RRBS-seq, proteomics and metabolomics;

  • to compare and contrast data from different “-omic” data collection approaches (genomics, transcriptomics, proteomics, metabolomics);

  • to evaluate strategies to characterize a genome/transcriptome/proteome/metabolome;

  • to design his own study (study and sample design, experimental planning) using suitable omics approach(es) to understand a certain biological question;

  • to evaluate the results of omics studies (e.g. analysis of datasets obtained by transcriptomics will be done);

  • to explain what normalization, data transformation…means and what it does to your data;

  • to explain the principles of some basic statistics such as t-test and false discovery rate

  • to explain the principles of PCA, when to apply and how to validate those models

  • to explain which tools are available for network and pathway analysis

Reading list/literatuur

Literature will be provided during the course.


Mw. Dr. S. Le Dévédec

Mode of instruction

The course will use a combination of lectures, discussions of assigned literature, computer-based exercises (workshops) and student-led presentations. Most of the courses will be offered in the morning and will focus on Omics technologies and their application in (pre-)clinical studies. Students will be expected to critically read assigned papers beforehand. There will also be hands-on how bioinformatics tools can be applied to analyze omics data output. Finally, students will also be expected to present a brief research proposal based upon their reading.

Assessment method

The course will be concluded by a presentation of a brief research proposal and a written exam. Students will be graded for the presentation (15%) and for the written exam (85%). In the written exam, there will be specific questions that will deal with the study material provided during the hands-on workshops; those questions will count for 15%. The remaining 70% are assigned to the questions from the various lecturers that presented during the entire course.

Admission requirements & Registration

This course is mandatory for students who do the Minor ‘Disease Signaling and Drug Targets’ (DSDT) and these students will be given priority. Ten additional places are available to students outside the minor under the condition that they meet the admission criteria. The same admission criteria apply to this course as for the entire Minor DSDT. Application for students outside the Minor DSDT occurs via the study advisers of Bio-Pharmaceutical Sciences only.