|Date||14 - 17 November 2016|
|Speaker(s)||Mark Ibberson, Frédéric Burdet, Leonore Wigger, Max Jan, and others|
|Cancellation deadline||19 Mar 2018|
The course will introduce the basic concepts of biological network analysis and provide practical instruction on commonly used bioinformatics tools to analyse and visualize biological networks. The course will start with a short symposium on biological network analysis covering network analysis and theory, visualization of complex networks and application to real biological problems. The symposium will be followed by theoretical and practical sessions where course participants will gain practical knowledge on how to perform different biological network analyses and how to visualize and interpret the results of such analyses.
This course targets biologists and bioinformaticians with some experience in analysing biological data. Intermediate level.
At the end of this course, participants are expected to be able to:
Knowledge / competencies:
Participants should have a basic working knowledge of R and be familiar with working with and manipulating biological data.
The registration fees for academics are 150 CHF. This includes course content material, coffee breaks and a social dinner. Participants from non-academic institutions should contact us before application. REGISTER HERE.
Deadline for registration and free-of-charge cancellation is set to November 5, 2016. Cancellation after this date will not be reimbursed. Please note that participation to SIB courses is subject to this and other general conditions, available here.
You will be informed by email of your registration confirmation. Upon reception of the confirmation email, participants will be asked to confirm attendance by paying the fees within 5 days.
University of Lausanne, Génopode Building, room 2020 (UNIL sorge M1 line stop)
Coordination: Grégoire Rossier (SIB), Corinne Dentan (UNIL/CUSO/Staromics)
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Morning - Short Symposium on Network analysis
Afternoon - Practical on network visualization and analysis in Cytoscape
Weighted gene correlation network analysis (WGCNA) - theory and practical
Network manipulation and analysis in R - theory and practical