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We would like to announce 3 training courses that will take place in Berlin in December. These involve training courses organised at LifeGlimmer for the systems biology and bioinformatics communities. The courses teach modelling and data handling using free open-source tools.

 

Course: Introduction to Linux command line tools 

1-Day-Course

23. February 2016, 9:00-17:00

LifeGlimmer GmbH, Berlin, Germany


This course will teach you basic shell commands to manage, edit, process and analyse your data even if you have never used the command line or Linux before.

In order to process, edit, or analyse your data, you can start out using generic tools like Microsoft Excel comma-separated value (csv) files. But when medium to large datasets become manifold, or working with them a necessary routine, you will quickly bump into the limitations of such common tools. Or you already did, and therefore you are reading this. No worries, we are here to furnish you with a set of data handling skills suited for the modern researcher. We will use one of the most powerful freely available tools for the job: the Linux shell. Even if you have never worked with Linux, you will quickly find out how smooth, fast, and efficient data processing can be with just a few simple commands.

Course: Fundamentals of modelling metabolism and signalling in biology

2-Day-Course

9.-10. February 2016, 1.-2. March 2016 9:00-17:00

LifeGlimmer GmbH, Berlin, Germany


This course will give an introduction to constructing and analysing basic metabolic and signalling models and expands on applying this on more complex systems using open source modelling software. Prior knowledge of modelling is not required.

Are you dealing with biological data which are related to metabolic or signalling networks and you wonder perhaps modelling will help you to gain more insights into your system? We offer a highly-condensed 2-day fundamental course to equip you with the essential know-how and hands-on experience to venture into computational modelling of metabolic and signalling networks. Without any prior experience about modelling, you will end up with necessary knowledge to start your own biological network model.

 

Day 1 of the training course will provide you with the essential knowledge and skills to be able to construct basic models and to analyse them using free open-source tools. This will give you an excellent outset from which to start exploring metabolic or signalling models that are of interest to you. With the widespread availability of omics technologies it has become feasible and practical to construct and analyse very big biological models, even up to the whole genome scale.

 

Day 2 will therefore provide you with ways in which to analyse more complex metabolic and signalling models, and also how to integrate them using open source tools. By the end of the course you will have the essential know-how and hands-on experience that allow you to venture into computational modelling of metabolic and signalling networks, both smaller models and on the whole-genome scale.

 

 

Course: Data processing of large biological datasets with command line tools

1-Day-Course

26. January 2016, 16. February 2016 9:00-17:00

LifeGlimmer GmbH, Berlin, Germany

This course will teach you how to use the shell commands grep, awk and sed combined with regular expressions to fast and efficiently process large datasets. Basic experience with the shell is recommended.


Nowadays, when working in modern biology, you often need to handle large datasets on a regular basis. Treat yourself to some powerful data handling skills suited for the modern biologist, using only free open-source tools.

You have some experience with Linux command line tools and want to extend your knowledge? This course will teach you how to use awk and sed efficiently combined with regular expressions. The theory will be illustrated with many hands-on excercises from the biological field. For instance, having over 1000 differentially expressed genes from a time series experiment and wanting to know which genes are more than 2-fold overexpressed at some point in time? With awk you will find those genes based on matching parameters. Wishing to visualise your genome scale metabolic model in Cytoscape, yet you made it with COBRApy? Using sed will properly get your data converted. You will practice on many more applications in hands-on examples

 

For more information, please visit: www.lifeglimmer.com/training