Modelling viruses: links and notes

This page is mostly for my own convenience, but if others find it useful too, so much the better. I would be very happy to hear from anyone who would like to comment, point me at relevant work, or collaborate in any way.

Hi to anyone who's here via Bronwen Dekker's blog! Here are the slides from the talk she heard.

Background

I am interested in the building of software models of viral infection: currently focusing on intracellular modelling, but ultimately aiming at the building of models which would connect intracellular models with intercellular models.

Systems biology background

I became interested in this challenge following discussions with Prof. David Harel, whose group has long been working on intercellular modelling. They have a system called GemCell which allows data-driven modelling of systems: fundamental intercellular behaviour is modelled generically in the system, parameterised on many relevant data which are provided for an individual model. The aim is to make it much easier than it has been to build a complex model, complete with, for example, simulation capabilities.

David visited Edinburgh on a grant led by Prof. Gordon Plotkin; one of the issues we were working on was how to extend GemCell's capabilities to the intracellular level. Would it be possible to take a similar data-driven approach to intracellular modelling, and connect intracellular with intercellular models? If so, how? If not, what would it take?

My own tentative conclusion (not necessarily shared by all on the project) is that the same level of data-driving is not to be expected at the intracellular level. The behaviours that we may need to model, and the abstractions we may need to make, are just too varied. We still needs good ways to make the building of intracellular models as easy as possible, however.

Viral infection struck me as an interesting area in which to look for case studies for this kind of work, for a number of reasons (not least that it's been an area of interest of mine for some years).

Software engineering background

My main field of research is software engineering, especially involving a different kind of model, prescriptive models of software systems (which may incorporate descriptive models of parts of their environment). In this environment, the engineering of the models throughout their lifetime is a major concern. For example, if we have two models which model the same system using different abstractions, they need to be kept consistent. If one is changed, perhaps because new information is discovered by the people mostly working with that model, then the other model may need to be changed to retain consistency. The field of (bidirectional) model transformations provides ways to record what consistency means in a particular case (e.g., which part of this model corresponds to which part of that one? Which elements of the models should be the same?) and how consistency should be restored. An open question is how much automation can really be done (economically/at all).

These engineering issues do not yet seem to be a major concern in the community that works with biological software models (? if you know differently, please let me know!) but if such models increase in importance, surely they will be.

Which virus?

A considerable amount of the literature (see below), especially that whose focus is the modelling itself, seems to be done in general terms, using an unnamed prototypical virus. That's reasonable - obviously a model engineering approach worth its salt has to be applicable to a wide range of viruses. For historical and pragmatic reasons, the virus I began by being most interested in was influenza. However, I am very happy to be beginning a collaboration with Dr Alain Kohl from Edinburgh's Laboratory for Clinical and Molecular Virology - he's most interested in arboviruses, such as Semliki Forest Virus, so that's currently where my focus is.

Modelling tools and techniques

Some relevant resources

Here are links to some relevant papers (many requiring subscription/payment). Rather scattergun at the moment: I would be most grateful to be told about other important relevant papers.

Random stuff...

Perdita.Stevens@ed.ac.uk