PhD position in Bioinformatics - Developmental And Reproductive Toxicity pathway

     
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WorkplaceLeuven, Flemish Region, Belgium
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PhD position in Bioinformatics - Developmental And Reproductive Toxicity pathway

If you are a bioinformatician with an interest in applying your knowledge of phylogenetics, omics data integration and data visualization to a societally relevant problem, apply to this PhD position.

The DART paths project

Assessment of developmental and reproductive toxicity (DART) requires many mammalian studies and particularly in this field of toxicology alternative(3R) test methods are highly warranted as they may have huge impact on the use of animals. Consequently many efforts have been put into the design of alternative assays and results of these efforts are very promising. The challenge however is that DART is extremely complex involving many diverse biological processes and interconnected adverse outcome networks. With the recent developments in molecular biology, -omics technologies, high throughput data-science and interconnectivity of databases this challenge can now be addressed. In the interdisciplinary project DART paths where both academic and industry partners play a role, the aim is to design a user-friendly web based interface that enables this complex data integration. The interface should allow in silico prediction and evaluation of DART, but also selection of the most relevant methods for non-animal testing for Wnt, BMP and other biological pathways that are essential in development.

The interface can be used starting from chemical(s), via adverse outcome networks, to a (predicted) DART phenotype, and from a DART phenotype backwards to adverse outcome pathways. This allows selection of relevant biological teststo predict DART or prioritize further investigation of certain chemicals. By linking & combining years of scientific research and knowledge that is available in public resources we aim to boost the acceptance of alternative testing in society.

 

Role of the PhD candidate

Theconservation of molecular pathways of several test species has been mappedagainst humans as reference, using automatically derived orthologousrelationships stored in the ENSEMBL comparative genomics database. We foundthat orthology prediction suffers from many shortcomings, especially forevolutionary more distant species such as D.rerio (zebrafish), C. elegans andD. discoideum that provideinteresting alternative test species. We have shown that to obtain realisticorthology relationships additional genomes should be included and high qualityphylogenetic reconstructions are necessary. The PhD candidate will makephylogenetic reconstructions for genes in pathways relevant to DART, to improvethe orthology assignments between human, animal test species and alternativetest models.

Furthermorethe student will be involved in mapping phenotypic information to molecularpathways. To map pathways to adverse outcomes, publicly available phenotypicinformation from mutants, knock-out and gene knock-down models will becollected for mouse, Zebrafish and C. elegans. Together with the industrialpartners a developmental stage visualization model will be developed thatenables alignment of pathways with gene(s) and phenotypic information acrossdifferent species. This will allow identifying AOP-related Molecular InitiationEvents (MIE) and Key Events (KE) starting from an adverse phenotype and thusselection of the best 3R tests to be used.

 

If you are a bioinformatician with an interest in applying your knowledge of phylogenetics, omics data integration and data visualization to a societally relevant problem, please send your cv and at least two reference letters to vera.vannoort [at] kuleuven[.]be

The Computational Systems Biology group led by prof. Vera van Noort is interested in understanding biological systems as a whole. We try to achieve this through computational analysis of large-scale data generated by the ever growing number of new technologies that can systematically measure the behavior of multiple cellular components, such as biochemical activities, biophysical properties, subcellular localization and interaction. We use and develop new methods to integrate, visualize and query the large amounts of information available and in such a way come to new biological discoveries.

The Computational Systems Biology group led by prof. Vera van Noort is interested in understanding biological systems as a whole. We try to achieve this through computational analysis of large-scale data generated by the ever growing number of new technologies that can systematically measure the behavior of multiple cellular components, such as biochemical activities, biophysical properties, subcellular localization and interaction. We use and develop new methods to integrate, visualize and query the large amounts of information available and in such a way come to new biological discoveries.

MSc in Bioinformatics/Computational biology with experience in phylogenetic reconstruction, python programming, high-performance computing and omics data visualization.

KU Leuven seeks to foster an environment where all talents can flourish, regardless of gender, age, cultural background, nationality or impairments. If you have any questions relating to accessibility or support, please contact us at diversiteit.HR [at] kuleuven[.]be.

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and reference  JobID 1031.