To understand large scale genomics results the Department of Bioinformatics - BiGCaT actively works on the development of tools that capture information about biological pathways at WikiPathways. The pathway information that is collected in this way can be used in pathway analysis for instance with our own tool PathVisio. The content of the pathways is directly linked to information about genes, proteins and metabolites from various databases using a mapping mechanism that is based on BridgeDb which was also developed in-house. These mappings are made available to the user of WikiPathways and to biologists doing pathway analysis, but that information currently does not include information about genetic variation.
There are several resources that contain information about known genetic variations, like dbSNP and SNPedia, and these are being expanded rapidly with data from large scale sequencing projects like the 1000 genome project and with information from projects focussing on genotype-phenotype relationships like the Human Variome Project. Integration of such information in pathway approaches is all the more important since large scale SNP, full exome and full genome information is nowadays often being collected as part of many biological studies and it would be good to be able to evaluate that data in an integrated way.
The project will therefore consist of two stages: 1) development of approaches to make genetic variation accessible in pathways for instance by connecting WikiPathways to the resources mentioned above and allowing the user access to that and 2) using that information to answer biological questions and develop the analytical tools to do so. While the first stage is thought to be relatively straightforward and can be started right away, the second stage depends on active collaboration in ongoing research projects and creative, need-based development of new approaches and tools.
Candidates should have a masters degree in a biological discipline with a strong background in modern genetics, including both the molecular and statistical aspects, and should also have affinity with using and developing computing approaches in collaborative open source projects and some proven experience in programming (ideally in Java). A more extensive background in computer science aspects like database theory, semantic web and graph theory will be a benefit but is not a prerequisite. They should be up to the challenge to do creative work on the front of modern systems biology and be prepared to do so as part of a team that spans our own group and many collaborating groups around the world.
Details and Application
Full details of this position, contact information, and how to apply can be found with this AcademicTransfer entry. Biostars working in the same group include Chris Evelo (group leader), Andra Waagmeester, and Egon Willighagen.