Building biological models automatically using the Semantic Web
| Building biological models automatically using the Semantic Web | |
|---|---|
status: finished
| |
| Student name: | student name::Timo Willemsen |
| Dates | |
| Start | start date:=2013/04/11 |
| End | end date:=2013/08/11 |
| Supervision | |
| Supervisor: | Anton Feenstra |
| Second supervisor: | Paul Groth |
| Second reader: | has second reader::Paul Groth |
| Thesis: | has thesis::Media:Thesis.pdf |
| Poster: | has poster::Media:Posternaam.pdf |
Signature supervisor
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Abstract
NOTE: This is a bachelor's project
The Semantic Web offers us a powerful mechanism for data integration. One (very) complex source of data are biological pathways and networks, e.g. for signalling and regulation. These networks are often used to model the biological system, e.g. using Petri nets.[1][2]
This project will explore the possibilities of a system for retrieval of pathway and network information using RDF queries and the automatic construction of Petri net models for the biological system. We will evaluate the feasibility of this approach based on two case studies for which we previously constructed working Petri net models. These are the MapK/Notch signalling pathway for cellular differentiation in C. elegans, and the beta-Catenin pathway involved in regulation of development in Humans (and many other species).
Related Projects
- Implementing GPCR signaling network model in Petri-Net (Michiel Vegt)
- Refining WNT/b-Catenin signalling network in Petri-net model (Matthias Seenok)
References
- ↑ Krepska E, et al. 2008 Krepska E, Bonzanni N, Feenstra KA, Fokkink W, Kielmann T, Bal H, Heringa J. Design issues for qualitative modelling of biological cells with Petri nets. In: Proceedings of the Formal Methods in Systems Biology 2008 (2008) 5054. Cambridge, UK: Springer. 48–62. of LNBI.
- ↑ Bonzanni et al. 2008 Bonzanni N, Krepska E, Feenstra KA, Fokkink W, Kielmann T, Bal H, Heringa J. Executing Multicellular Differentiation - Quantitative Predictive Modelling of C elegans Vulval Development Bioinformatics. 2009 25:2049-56.
