NGFN-PLUS
Gene data mining platform and statistics
| Coordinator: | Prof. Dr. Roland Eils, Prof. Dr. Andreas Zimmer | |
| Institution: | DKFZ Heidelberg, Universität Bonn | |
| Homepage: | www.dkfz-heidelberg.de/ibios |
Gene data mining platform:
For the purposes of pooled analyses a common database to include the different genetic and transcriptomic information on alcohol drinking and addictive behaviour will be established. The cross platform and cross species (mice, rats, humans) information will be unified to render integrative analyses possible. The data will be subsequently analysed in our subproject and also contributed to SP3 “Computational Modelling” (Matthäus, Jäger) where the genomic and transcritomic information is incorporated into a computational model to simulate molecular networks, disease progression and therapeutic response. Utilising this platform, new molecular candidate networks, neurochemical systems, and pathways involved in the aetiology of alcohol addiction will be investigated. Through function based analysis, associated candidate genes will be defined. Furthermore, based on analyses of the transcriptional regulation and the underlying regulatory networks candidates will be investigated. Using data on genetic aberrations, predispositions to addictive behaviour will be examined. An integrative analysis over different organisms and different data types, such as gene expression, genetic background, and mutation effects will be conducted. Resulting candidates and molecular networks and neurochemical systems will be validated in genetic animal models (Schu?tz, Wurst, Deusing, Zimmer, Bartsch, Spanagel; SP4-8). Furthermore, validated candidates will be transferred to human genetic studies in SP10 and 12 (Rietschel, Nöthen, Dahmen, Wichmann).
Genetic epidemiology platform:
Recently, genome-wide association studies (GWAS) have become the prevalent systematic and hypothesis-free approach to the detection of susceptibility variants in complex diseases. Under a typical case-control design involving 500 to 2,000 individuals in both subsamples, 500,000 to 1,000,000 SNP markers are genotyped on each DNA sample using highthroughput microarray-based chip technology. SP11 and SP12 will use this approach within the IG, and, following a stringent design based on extensive statistical power calculations, aim at the detection and characterization of etiologically relevant genes.
Further Coordinators:
For the purposes of pooled analyses a common database to include the different genetic and transcriptomic information on alcohol drinking and addictive behaviour will be established. The cross platform and cross species (mice, rats, humans) information will be unified to render integrative analyses possible. The data will be subsequently analysed in our subproject and also contributed to SP3 “Computational Modelling” (Matthäus, Jäger) where the genomic and transcritomic information is incorporated into a computational model to simulate molecular networks, disease progression and therapeutic response. Utilising this platform, new molecular candidate networks, neurochemical systems, and pathways involved in the aetiology of alcohol addiction will be investigated. Through function based analysis, associated candidate genes will be defined. Furthermore, based on analyses of the transcriptional regulation and the underlying regulatory networks candidates will be investigated. Using data on genetic aberrations, predispositions to addictive behaviour will be examined. An integrative analysis over different organisms and different data types, such as gene expression, genetic background, and mutation effects will be conducted. Resulting candidates and molecular networks and neurochemical systems will be validated in genetic animal models (Schu?tz, Wurst, Deusing, Zimmer, Bartsch, Spanagel; SP4-8). Furthermore, validated candidates will be transferred to human genetic studies in SP10 and 12 (Rietschel, Nöthen, Dahmen, Wichmann).
Genetic epidemiology platform:
Recently, genome-wide association studies (GWAS) have become the prevalent systematic and hypothesis-free approach to the detection of susceptibility variants in complex diseases. Under a typical case-control design involving 500 to 2,000 individuals in both subsamples, 500,000 to 1,000,000 SNP markers are genotyped on each DNA sample using highthroughput microarray-based chip technology. SP11 and SP12 will use this approach within the IG, and, following a stringent design based on extensive statistical power calculations, aim at the detection and characterization of etiologically relevant genes.
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