General
Section outline
-
Machine learning for bioinformatics and computational biology
Lausanne, 23-27 February 2015
Overview
This course introduces the theoretical basis of several important machine learning algorithms used in bioinformatics and illustrates them with examples of applications in the field of genomics, signalling networks, population genomics, text mining.
Objectives
Upon completion of this course, you will understand the statistics components and theory of machine learning algorithms. You will also know how to evaluate machine learning parameters and how to apply these tools to biological problems.
Recommended background: Knowledge requirements: basic mathematical background, knowledge of R and one scripting programming knowledge (Python or Perl for example).
Technical requirements: Laptop with R version 3.1.1 and Matlab installed, 3 GB of free disk space, sbv Improver account (register at https://sbvimprover.com/). Some data files will have to be downloaded before the course, precise instructions will follow later. In the case your university does not provide Matlab licenses, please contact us training@isb-sib.ch.
Application
We had many more applications than we could host. We are not accepting registrations any more.
As the number of seats is limited we are confirming registrations individually. If you didn't receive a confirmation so far, is because your name is on the waiting list.
The registration fees for academics are 200 CHF. This includes course content material and coffee breaks. Participants from non-academic institutions should contact us before application.
Deadline for registration and free-of-charge cancellation is set to the 9 February 2015.
Location
Genopode Building
Additional information
We recommend 1 ECTS credits for this course in the case the exam, at the end of the session, is successfully passed.
You are welcome to register to the SIB courses mailing-list to be informed of all future courses and workshops, as well as all important deadlines using the form here.
For more information, please contact training@isb-sib.ch.