
| Location | Maastricht6200 MDLimburg |
|---|---|
| Scientific fields | Natural Sciences, Engineering, Health, Food |
| Function types | Postdoc positions, Research, Development, Innovation, Education |
| Education | Doctorate |
| Hours | 38.0 hours per week |
| Salary | € 2861 - € 4970 |
| End procedure | 26 February 2010 |
| Job number | AT2010.9 |
| Translations | en |
An important aspect of life is that genes respond to the environment. Disease, diet, exercise, and exposure to toxic compounds or even psychological stress are examples of life and life style factors that influence gene expression regulation. Oftentimes the effects on gene regulation are small but related. Specific biological pathways are affected and the way in which they are affected is determined by genetic factors (what exact genes does an individual have) and previous epigenetic imprinting of the genome.
Because the biological effects often occur for related gene products and metabolites and thus in biological pathways, pathway analysis is very important for the understanding of the outcome of many studies, especially those using genomics approaches. Recently, our department, in collaboration with the University of California, San Francisco, introduced Wikipathways a community based pathway platform to develop and curate pathways (www.wikipathways.org). The content was developed by many domain experts.
The focus of the postdoc position is on the integration of various types of available biological information by making use of network analysis. A commonly used tool for visualizing, modeling and analyzing molecular and genetic interaction networks is the free software package Cytoscape. Cytoscape is very flexible and allows users to extend its functionality by creating or downloading additional software models called “plugins”. The networks can be analyzed by identifying putative functional and structural modules. A connection between Wikipathways and Cytoscape is already realized, enabling the exchange of information.
First of, all the interactions between gene products and metabolites present in Wikipathways and information available in genomics repositories should be integrated. By integrating these information repositories a complete overview of interactions can be generated. One should keep in mind that more data doesn’t always give you a better understanding of the mechanism but it can make it more complex. Therefore, it is necessary to select the most important information. This filtering can be done in several ways.
Second, additional information on relatively new gene and protein regulation should be added to the pathways in WikiPathways. Regulation of gene expression and proteins occurs at several levels by for example transcription factors and microRNAs. Various databases describe target sites for these gene regulators. By coupling the information on the target sites to the genes present in the pathways the regulation can be incorporation taking the visualization and analysis of pathways to the next level.
Third, a single nucleotide polymorphism (SNP), which is a variation of a single nucleotide in a DNA sequence on population level, can be related to a certain disease state or susceptibility to pathogens. Genes within the pathways should be linked to important SNPs. This will enable the analysis of SNP arrays and in the near future sequencing studies. The postdoc will collaborate with excellent researchers in nutrigenomics and nutrigenetics to use the dataintegration approaches developed in real life studies and will visit some of the research groups involved.
Bioinformatics is evolving rapidly. One should keep up with novel techniques and methods. This makes Bioinformatics a challenging research field with new and exciting opportunities.
The candidate should have a PhD in Bioinformatics, Medical Biology or related field. He or she has a strong affinity with data integration, network and pathway analysis. An interest in online cooperation in open source development should be present. He or she should feel the new developments in genomics and systems biology as a challenge. In addition, excellent communication skills, both oral and written and a good knowledge of English are necessary.
The terms of employment of Maastricht University are set out in the Collective Labour Agreement of Dutch Universities (CAO). Furthermore, local UM provisions also apply. For more information look at the website http://www.maastrichtuniversity.nl/ , go to “Prospective employees” and than “UM as an employer”. Here you will find the terms of employment.
A 4-year full-time position for a postdoc is currently vacant. Salary will be according to standard levels for postdocs and depending on experience.
Temporary
4 years
Maastricht University is renowned for its unique, innovative, problem-based learning system, which is characterized by a small-scale and student-oriented approach. Research at UM is characterized by a multidisciplinary and thematic approach, and is concentrated in research institutes and schools. Maastricht University has around 14,000 students and 3,500 employees. Reflecting the university's strong international profile, a fair amount of both students and staff are from abroad. The university hosts 6 faculties: Faculty of Health, Medicine and Life Sciences, Faculty of Law, School of Business and Economics, Faculty of Humanities and Sciences, Faculty of Arts and Social Sciences, Faculty of Psychology and Neuroscience.
NUTRIM, department of Bioinformatics
NUTRIM, department of Bioinformatics
NUTRIM School for Nutrition, Toxicology and Metabolism is part of the Faculty of Health, Medicine and Life Sciences of the Maastricht University. NUTRIM initiates and catalyzes translational research into nutritional health benefits and risks focusing on metabolic and chronic inflammatory diseases. There are 15 departments incorporated within NUTRIM, amongst them the bioinformatics department (BiGCaT). The total number of staff (scientific and support staff) participating within NUTRIM is approx. 245 including some 120 PhD students. Within the bioinformatics department de main focus is to help understand the meaning of “omics” data, to integrate the knowledge needed to do that, to develop novel analysis methods and to apply all of that in ongoing biomedical research.
Dr. CTA Evelo (head of the bioinformatics department)
+31-43-3881231 (direct), +31-43-3881999 (secretary)
The short URL code for this job opening is: 3044
Direct link to this job www.academictransfer.com/3044
