Uncategorized

22/01/2018

Drug Screen Meeting

Date: 18th-20th February 2018
Venue: Gut Lilienfein
Wieden

Sunday, 18th February 2018

19:30 – 21:00 Informal à la Carte Dinner in the hotel restaurant. No fixed arrival time for the participants.

 

Monday, 19th February 2018

08:30 Welcome. Sascha Dietrich, Wolfgang Huber and Thorsten Zenz
08:40 – 09:00 Round table – introduction. All

Session I, scientific presentations

(15’ presentation + 5’ discussion)

09:00 – 09:20 Talk 1. Jennifer Hüllein (EMBL)
09:20 – 09:40 Talk 2. Junyan Lu (EMBL)
09:40 – 10:10 Talk 3. Kwang Lee and Aleksander Slusarczyk (NCT)
10:10 – 10:40 Coffee break
10:40 – 11:00 Talk 4. Vineet Dalal (NCT)
11:00 – 11:20 Talk 5. Alexander Jethwa (NCT)
11:20 – 11:40 Talk 6. Alice Fu (NCT)
11:40 – 12:00 Discussion
12:00 – 13:00 Lunch
13:00 – 17:00 Outdoor activity
18:00 – 20:00 Dinner
20:00 – 20:30 Feedback and strategy. Group leaders
20:30 – 20:50 Talk 7. Almut Lütge (University of Heidelberg and EMBL)
20:50 – 21:10 Talk 8. Sophie Rabe (NCT)
21:10 – 21:40 Talk 9. Peter Bruch (NCT) and Holly Gilles (EMBL)
21:40 Networking

Tuesday, February 20th 2018

Session II, scientific presentations

(15’ presentation + 5’ discussion)

09:00 – 09:20 Talk 10. Vladislav Kim (EMBL)
09:20 – 09:40 Talk 11. Dorothee Childs (EMBL)
09:40 – 10:00 Talk 12. Laleh Haghverdi (EMBL)
10:00 – 10:30 Coffee break
10:30 – 10:50 Talk 13. Marta Stolarczyk (NCT)
10:50 – 11:10 Talk 14. Tobias Roider (NCT)
11:10 – 12:15 Discussion and plans for drug screen research at EMBL, NCT and USZ in 2018
12:15 – 13:00 Lunch
13:00 Departure

 

27/02/2017

CSAMA 2017 – Statistical Data Analysis for Genome Scale Biology

CSAMA 2017 (15th edition)
Statistical Data Analysis for Genome Scale Biology
Bressanone-Brixen, Italy (South Tyrol Alps)
June 11-16, 2017

Lecturers:

  • Simon Anders, University of Heidelberg
  • Jennifer Bryan, RStudio and UBC
  • Vincent J. Carey, Harvard Medical School
  • Laurent Gatto, University of Cambridge
  • Wolfgang Huber, European Molecular Biology Laboratory (EMBL), Heidelberg
  • Martin Morgan, Roswell Park Cancer Institute, Buffalo
  • Johannes Rainer, European Academy of Bozen (EURAC)
  • Charlotte Soneson, University of Zurich
  • Levi Waldron, CUNY School of Public Health at Hunter College, New York

Teaching Assistants:

  • Simone Bell, EMBL, Heidelberg
  • Vladislav Kim, EMBL, Heidelberg
  • Lori Shepherd, RPCI, Buffalo
  • Mike L. Smith, EMBL, Heidelberg

The one-week intensive course Statistical Data Analysis for Genome-Scale Biology teaches statistical and computational analysis of multi-omics studies in biology and biomedicine. It covers the underlying theory and state of the art (the morning lectures) and practical hands-on exercises based on the R / Bioconductor environment (the afternoon labs). At the end of the course, you should be able to run analysis workflows on your own (multi-)omic data, adapt and combine different tools, and make informed and scientifically sound choices about analysis strategies.

Topics include:

  • Introduction to R and Bioconductor
  • The elements of statistics: hypothesis testing, multiple testing, regression, regularization, clustering and classification, parallelization and performance (machine learning), visualisation
  • RNA-Seq data analysis
  • Computing with sequences and genomic intervals
  • Working with annotation – genes, genomic features, variants, transcripts and proteins
  • Gene set enrichment analysis
  • Mass spec proteomics and metabolomics
  • Basis of microbiome analysis
  • Experimental design, batch effects and confounding
  • Reproducible research and workflow authoring with R markdown
  • Package development, version control and developer tools (incl. git, github, RStudio)
  • Working with large data: performance parallelisation and cloud computing

The course consists of

  • morning lectures: 20 x 45 minutes: Monday to Friday 8:30h – 12:00h
  • 4 practical computer tutorials in the afternoons (13:30h – 16:30h) on Monday, Tuesday, Thursday and Friday

Visit the course’s website at: http://www.huber.embl.de/csama