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  Association mapping of complex phenotypes using models at a systems level

Stegle, O. (2010). Association mapping of complex phenotypes using models at a systems level. Talk presented at Workshop Statistical and Dynamical Models in Biology and Medicine. Heidelberg, Germany. 2010-10-21 - 2010-10-22.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0002-AF95-1 Version Permalink: http://hdl.handle.net/21.11116/0000-0002-AF96-0
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 Creators:
Stegle, O1, 2, Author              
Affiliations:
1Former Research Group Machine Learning and Computational Biology, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528696              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497794              

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 Abstract: The goal of genetic association studies is to relate polymorphic genetic loci to quantitative traits that capture the phenotypic variation of interest. While this task is well studied for "simple" univariate phenotypes, recent high-dimensional phenotypes ask for more advanced modeling techniques at a systems level. In this talk I will discuss recent machine learning techniques to address these emerging challenges and illustrate them using two case studies. First, I will focus on QTL mapping of high-dimensional microarray data in yeast. In this setting, inference of unmeasured transcription factor activations from the expression levels and pathway information allows the phenotypic variation to be dissected at a previously unavailable level of detail. Second, I will discuss mapping techniques for the treatment response of human depressed patients. In these data, the joint modeling of observations that change over time and complex confounding influence need to be taken into account to identify relevant genetic markers.

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 Dates: 2010-10
 Publication Status: Published in print
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Title: Workshop Statistical and Dynamical Models in Biology and Medicine
Place of Event: Heidelberg, Germany
Start-/End Date: 2010-10-21 - 2010-10-22
Invited: Yes

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Title: Workshop Statistical and Dynamical Models in Biology and Medicine
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 8 Identifier: -