Topics in Computational Biology & Analysis of Scientific Data using R

Lecture room: GPS Google maps link, OG 1.

OBJECTIVE

Conscious and well-considered handling of scientific projects by computational methods (primarily R based).

EXAMPLE

Get to grips with the difficult R fundamentals, learn how to set up workflows and develop a deep understanding of gene expression analysis (basics 60%, workflow 40%).

PREREQUISITES

None - but some interest in theoretical work and the software supporting such type of work is necessary.
For practice at home a notebook or PC is necessary.

REQUIREMENTS

The first period will be also a pre-meeting to clarify the requirements for the seminar.

ENROLL IN THIS COURSE

Register with this registration form by email.
Deadline of registration: date of the regular start of the lecture period.

ABSTRACT

The field of computational biology is mainly based on programming languages, algorithms and applied mathematics. In this course we focus on the mathematical language R and try to learn step by step the philosophy of theoretical work and the art of computing including algorithms and mathematics/statistics.
Because this course mostly faces the situation that beginners and experienced students / scientists come together, we start every semester with the basics and evolve to advanced projects over time.
The reason for offering such an interdisciplinary and theoretical course for advanced students and post graduate researchers at the medical faculty, but also open for the natural science faculties, is based on the raising complexity in the life sciences and the increased use of theoretical methods. To bridge the existing gap between medical sciences and this highly theoretical field, the course is based on interactivity and a course level adjusted to the needs of the participants. Therefore we also encourage people with research interests in the experimental life sciences to join this course even if they to not expect to work on this field, to improve their insight into the methods and philosophy of bioinformatics / systems biology.
The audience is also encouraged to make their own proposals.
As per request we might extend to other processing languages too.

RESOURCES

A server with present and past course resources is available.

COURSE STAFF

Prof. Korsching.

CREDITS

Elective course certificate.
It is based on an exam talk with R code. The live R projects, should not (entirely) be a pure 1:1 copy of the seminar to that point. The R source file(s) + explanatory slides need to be send to the course instructor. Certificates will be available the week thereafter in the office of the institute by Sandra Holert.
Attendance at all seminar hours is compulsory. Absence notification by email mandatory.