organized by Tim Beißbarth
Statistical methods are crucial in many bioinformatics problems and applications. Especially the analysis of large scale omics data requires not only massive computation and efficient algorithms, but also relies on solid statistical methodology. The two scientific associations, i.e. the German Society on Medical Informatics, Biometry and Epidemiology (GMDS) and the German region of the International Biometric Society (IBS), have therefore established a joint working group that aims to coordinate the activity of the active members that are working on the border between bioinformatics and biostatistics by organizing regular workshops and other common activities.
Here, in this workshop several talks should present topics coming from the main themes that have been in the focus of this working group in recent years. Especially these topics include methods for statistical analysis of high-throughput omics data, machine learning approaches on high-dimensional data and methods for network reconstruction.
Please contact tim.beissbart(at)ams.med.uni-goettingen(dot)de for more information.
The workshop takes place on 10 September 2013 on Göttingen's North Campus, lecture hall HS1 at the Faculty of Physics.
Abstracts of talks can be downloaded here.
|Rainer Spang (Functional Genomics, University of Regensburg)
Modeling signaling networks with unknown unknowns
|Lars Kaderali (IMB, Dresden University of Technology)
Individual Cell Population Context in RNAi Data Analysis
|Holger Fröhlich (Algorithmic Bioinformatics, University of Bonn)
Network and Data Integration for Biomarker Signature Discovery via Network Smoothed T-Statistics
|Maral Saadati (Biostatistics, DKFZ Heidelberg)
Statistical Challenges of High Dimensional Methylation Data
|Manuela Zucknick (Biostatistics, DKFZ Heidelberg)
Integrated risk-prediction modelling based on multiple genomic data sources with Bayesian variable selection models
|Yinyin Yuan (The Institute of Cancer Research, London, UK)
Integrative Modeling of Cancer-Immune Interactions in Triple-Negative Breast Cancers
|Julien Gagneur (Gene Center, LMU Munich)
Inferring causal molecular intermediates from omics data in the context of genetic and environmental variations
|Pratyaksha Wirapati (Bionformatics, Swiss Insitute of Bioinformatics)
Challenges in development of practical omics biomarkers for risk prediction
|Klaus Jung (Medical Statistics, UMG Göttingen)
Global Tests for Expression Data of Molecular Subsets in High-Throughput Experiments