Machine learning for bioinformatics and computational biology
Lausanne, 23-27 February 2015
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.
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 firstname.lastname@example.org.
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.
We recommend 1 ECTS credits for this course in the case the exam, at the end of the session, is successfully passed.
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