A systems analysis of rodent animal models
PhD student: A systems analysis of rodent animal models of human disease
Function title PhD student Where Bioinformatics Laboratory, Academic Medical Center, Amsterdam Apply before July 15, 2009 Project Model organisms have been essential for improving our knowledge of human disease. Especially rodents, mainly mouse and rat, are often used for this purpose, as well as for pre-clinical trials of new drugs and toxicology screens.
However, often animal models fail to mimic human disease adequately. As a consequence drugs successfully tested in animal models fail in costly clinical trials or are falsely discarded. Goal of this project is to explore the suitability of rodents as a model organism for human disease, specifically metabolic syndrome. Since metabolic syndrome is a complex multifactorial group of metabolic conditions, a systems approach will be taken to uncover the molecular networks perturbed by disease. Specifically, we aim to validate the similarity of a large number of rodent models for metabolic syndrome to their human counterparts. The project is tightly linked to ongoing projects in biological and clinical groups at the AMC. This project is
part of the second round of the BioRange programme of the Netherlands Bioinformatics Centre (NBIC; www.nbic.nl).
Tasks The successful candidate will work towards a PhD degree in bioinformatics. We will build a compendium of rodent and human metabolic syndrome related gene expression datasets. We develop module-based joint analysis methods that search for conserved patterns consisting of sets of genes and sets of conditions in both rodent model and human under which they are co-expressed. These patterns are used to evaluate the molecular similarity of rodent models and their human counterpart.
Conserved patterns will be further interpreted by constructing functional networks for metabolic syndrome in rodents and human. We expect methods developed and resulting conserved patterns and functional networks to be useful for elucidating the model mismatch and for increasing the predictive value of preclinical trials and toxicity screens.
Requirements :
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Function title PhD student Where Bioinformatics Laboratory, Academic Medical Center, Amsterdam Apply before July 15, 2009 Project Model organisms have been essential for improving our knowledge of human disease. Especially rodents, mainly mouse and rat, are often used for this purpose, as well as for pre-clinical trials of new drugs and toxicology screens.
However, often animal models fail to mimic human disease adequately. As a consequence drugs successfully tested in animal models fail in costly clinical trials or are falsely discarded. Goal of this project is to explore the suitability of rodents as a model organism for human disease, specifically metabolic syndrome. Since metabolic syndrome is a complex multifactorial group of metabolic conditions, a systems approach will be taken to uncover the molecular networks perturbed by disease. Specifically, we aim to validate the similarity of a large number of rodent models for metabolic syndrome to their human counterparts. The project is tightly linked to ongoing projects in biological and clinical groups at the AMC. This project is
part of the second round of the BioRange programme of the Netherlands Bioinformatics Centre (NBIC; www.nbic.nl).
Tasks The successful candidate will work towards a PhD degree in bioinformatics. We will build a compendium of rodent and human metabolic syndrome related gene expression datasets. We develop module-based joint analysis methods that search for conserved patterns consisting of sets of genes and sets of conditions in both rodent model and human under which they are co-expressed. These patterns are used to evaluate the molecular similarity of rodent models and their human counterpart.
Conserved patterns will be further interpreted by constructing functional networks for metabolic syndrome in rodents and human. We expect methods developed and resulting conserved patterns and functional networks to be useful for elucidating the model mismatch and for increasing the predictive value of preclinical trials and toxicity screens.
Requirements :
read more
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