Analyse von großen Datensaetzen in den Lebenswissenschaften - SS15

We will use "slack" as our communication platform. Please sign up here: https://bigdatainlifesciences.slack.com/signup

 
Summary

This course is about running a real life project analysing large data-sets from the life-science and interpreting the results. (More information here.)

Lectures
  • Wednesday, 8:30-10h: Lecture (Arnimallee 6, SR 007)
  • Wednesday, 14:15-18h: Lab Session (Arnimallee 6, SR 017)

(All sessions start at the given times.)

 

Sessions


Each of the modules will contain a theoretical and a practical part and will vary in number of individual sessions.

 

# Module Topics Suggested Reading
1 Big Data & Life Science Data infrastructure: storage, access, databases, and data standards; compute infrastructure: processors, clouds, and workflows; scalable algorithmics: searching, streaming, and randomized or parallel algorithms; map-reduce
 
2 Analysing large biological data-sets
 

Data mining: From raw data to gene lists: data normalization, processing and signal extraction. From (classical) statistics to compressed sensing and matrix completion.
 

 
3 Genes and pathways Gene-set and pathway enrichment analysis
 
 
4 Network analysis and visualization
 
Network-based analysis
 
 
5 Data integration Bayesian and network-based data integration and fusion
 
 
6 Disease detection & analysis Classification, gene function prediction, TPT
 
 

 

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An Adobe Acrobat file BigData in Life-Sciences - Assignment 1 Download Preceding File Preview in Google Docs Viewer 72.67 KB 2015-04-29 13:48:21
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