Johannes Werner (DKFZ) Jules Kerssemakers (DKFZ) Malvika Sharan (EMBL) (HD-HuB)

24-26 July, 2017

Heidelberg Center for Human Bioinformatics (HD-HuB) Institute of Pharmacy and Molecular Biotechnology (IPMB) 5th floor, Im Neuenheimer Feld 364, 69120, Heidelberg

Python has grown in the last ten years to become one of the most widely-used programming languages in biology. This increasing popularity reflects how easy Python is to learn compared with other languages, and how adaptable it is to a wide variety of different tasks. Simultaneously, the rise of data-driven approaches to science means that programming skills are becoming more and more important for biologists.

Course content:
- The basic concepts and building blocks of programming in Python
- Automating repetitive tasks and calculations
- Handling different types of data using the concept of Data Structure Reading and handling data from a file
- Introduction to Python modules
- Introduction to the regular expression
- An optional half day supervised practice session will be offered for the participants to work on their dataset or specific problems

After attending the course, you will have a good understanding of the core themes of programming, and be able to write your own Python programs, to automate repetitive analysis tasks.

Learning goals:
This course aims to teach basic programming skills to the life-scientists, who wish to carry out repeated tasks to deal with biological data. The goal of the course is to enable them to use Python scripting to automate their tasks and carry out analysis of their data reproducibly.

We do not expect the participants to have any prior knowledge with scripting. This is a course for the researchers, who wish to automate their tasks such as dealing with large number of files to carry out identical or similar analysis using Python programming language.

The computers will be available at the workshop venue, but participants can bring their own laptop with the Anaconda Python Distribution (version 3.5) installed.

Programming; Bioinformatics; Data Analysis; Python; Data-handling Tools: Python, Anaconda Python distribution 3.5

Malvika Sharan
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