1. Systems Modelling of EMT Cell Signalling Pathways in Heart Valve Development Tariq Abdulla 1, Ryan Imms 1, Jean-Marc Schleich 2 and Ron Summers 1 VPH 2010 01/10/2010 1 Dept. Electronic and Electrical Engineering, SEIC, Loughborough University, LEICS, UK, LE11 3TU E-mail: T.Abdulla@lboro.ac.uk Web: http://www-staff.lboro.ac.uk/~elta2 2 LTSI, University of Rennes 1, Rennes, F-35000, France

2. “Epithelial to Mesenchymal Transition” 2

3. Outline  Heart Development – what happens?  Heart Looping  Neural Crest Cell Migration  Endocardial Cushion Growth  Congenital Heart Defects  Systems Modelling - how do we do it?  Conceptual Model  Network Modelling  Tissue Modelling  Integration  Conclusion and Future Work

4. Heart Development: what happens? Rear View

5. Membranous Septum Muscular Septum

6. Neural Crest Cell Migration

7. Endocardial Cushion Growth

8. 8

9. Heart Development: what happens?

11. Systems Modelling – how do we do it?  Different types of computational model are suitable for different levels of biological scale  E.g. Biochemical reactions can be represented as networks or ODEs. Cellular behaviour can be modelled with agent based models.  Use models at one level of scale, to pass information to models at another level of scale

12. Conceptual Modeling

14. Network Modelling 14 KEGG

15. 15

16. Notch Signalling 16

17. Notch Signalling 17

18. 18

19. Tissue Modelling 19  Tissues are often modelled as though they are continuous  But many of the interesting things that happen in tissues are to do with individual cell behaviour, and social behaviour (structure)  When there is an abnormality at tissue level we may need to know whether this is hypotrophic (fewer cells) or hypoplastic (smaller cells)

20. Tissue Modelling 20  A lot of the movement of cells around each other, and how they interact, can be explained by their relative adhesiveness to other cells  This is the Differential Adhesion Hypothesis

21. Compucell3D

23. Integration  We take a proactive approach in model annotation, and are even developing methods for multiscale annotation  This includes combining terms from multiple reference ontologies in post-composition  Use of common formats such as SBML

25. 25 Molecules Cells Tissues Organs ? PMR2 Ontologies

26. Conclusion and Future Work  Modelling systems of such complexity is difficult, but it’s essential if we are to understand them  Comparison with in vivo or in vitro data is essential for model validation and improvement  This project has the potential to be applied to tissue engineering

27. Questions or suggestions?

28. Thanks to (in no order):  Ron Summers  Ryan Imms  Jean-Marc Schleich  Fanny Bajolle  Lucile Houyel