Course teacher(s)
Vincent DETOURS (Coordinator)ECTS credits
5
Language(s) of instruction
english
Course content
The course starts by presenting microarray technologies and the preprocessing steps required before any biological investigation can be carried out. Next, I introduce methods basically extending the pre-genomics, low-throughput gene expression experiments to genome-wide screens. Then the course unfolds with the presentation of recent tools that operate, not at the level of individual gene, but at the level of functionally related gene sets and global molecular phenotypes. More specifically we will learn about:
-microarray normalization
-
sequence alignment for next generation sequencing-selection of differentially expressed genes-gene set analysis methods-supervised and unsupervised classification of genome-wide expression profiles-typical statistical illusions that come with the above,-If time allows, transcriptome sequencing will be overviewedComputational methods will be introduced together with the research problems drawn mostly from oncology research. Thus, the student will learn for example:-to what extent the glogal gene expression varies among different human populations,-how to predict cancer outcome from gene expression profile,-how to establish connection between drugs and biological conditons from gene expression databases,-etc.
Objectives (and/or specific learning outcomes)
Provide conceptual tools for a critical assessment of the functional genomics literature. Introduction a several important databases. Reproduce elementary, but wide-spread functional genomics data analysis schemes.
Teaching methods and learning activities
The course does not present a nicely polished texbook view of science, but science in the making with its ectics, turn arounds and controversies. Lectures are interupted by hands-on exercises in which the student actually use the methods on real life data and reproduce published research results.
Students are empowered to conduct their own analysis by reproducing the bioinformatics analysis of a published study.
Contribution to the teaching profile
Master in-depth scientific knowledge to understand a problem scientific research and the questions it asks, identify the most relevant experiences and the most appropriate techniques to meet them.
To master a new field of research, to be creative, to be able to be critical and to write a research project.
Master the basic scientific techniques of biomedical research that will enable him/her to develop and implement an experimental approach, to compare its results forecasts, and to assess the validity limits of its model. Plan and organize the successive stages of an experimental protocol and validate it.
Be autonomous, organize and manage your time, plan and prioritize your work.
Use study tools (including bioinformatics tools) in the biomedical sciences and main measuring instruments and to identify sources of errors.
Read the English language scientific literature fluently and search for it
relevant.
To argue, to write a synthesis of its results in French and English and to consider perspectives including French and English, cite sources and ban plagiarism
Present correct and consistent scientific information.
Interact with peers, share and argue the research developed, including in English.
To be able to read, interpret, criticize a scientific article
To question oneself, to be critical, to debate, to debate and / or to defend one's ideas.
Consider ethical issues and apply ethical behavior.
References, bibliography, and recommended reading
NA
Other information
Contacts
vdetours@ulb.ac.be
Evaluation
Method(s) of evaluation
- Other
Other
-
Project report, 50%
-
Oral exam, 50%
Mark calculation method (including weighting of intermediary marks)
-
Project report, 50%
-
Oral exam, 50%
Language(s) of evaluation
- english
- french