Events and Conferences

Titus Brown's Data Intensive Biology Training Program Workshops

January 27, 2016
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SFU will be holding several half-day workshops as part of Titus Brown's Data Intensive Biology Training Program.

These workshops will be hands on and you will be supported by several TAs in addition to the instructor.

All are welcome to participate, regardless of discipline or training level. Although examples will be focused on biology, non-biologists are also welcome to participate.

For more information and how to register, please see below:

Regular Expressions and Python taught by Tiffany Timbers on Feb 17, 2016

  • In this workshop, we will explore examples of using regular expressions find transcription factor binding sites, as well as to find regions of phage DNA (spacers) in bacterial genomes - key parts of the CRISPR bacterial immune system. We will also explore how to build a test suite for regular expression searches to ensure the regular expression pattern matching is accurate. 

    For more information, please see here.  
    Register here.

Amazon Web Services taught remotely by Titus Brown (UC Davis) on Mar 7, 2016

  • Learn how to use Amazon web services to compute remotely, as well as how this service can be used for reproducible research. 

    Register here

R Markdown taught remotely by Marian Schmidt (U. Michigan) on May 11, 2016

  • What is robust and reproducible research? How can you make your research more robust and reproducible? You can use RMarkdown! Wait, what’s RMarkdown? RMarkdown is a variant of Markdown that has embedded R code chunks to be used with knitr to make it easy to create reproducible web-based reports. 

    Register here

Open Science taught locally by Bruno Grande (SFU) on June 13, 2016

  • How much code do you think is written in your lab that never makes it under version control? The ideal answer is none, but realistically, it might be most if not all. This workshop will introduce you to strategies and workflows to make not only your code, but many aspects of your research more transparent, reproducible and open. 

    Register here

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