Professor Vincent Jansen
My research is about the mathematical modelling of biological systems. My main interest is in the modelling of population dynamics and its consequences for evolution. I am currently working on the following projects:
Current Projects:
1. Evolution in structured environments
The modelling framework used in Jansen and Mulder (1999), Bonsall et al. (2004) and Jansen and Vitalis (2007) can be generalised to study evolution in patchy environments for a very large class of local dynamics. The model combines within patch dynamics with dispersal between patches which allows for kin or group selection to occur. This model differs from other models for kin selection in that a realistic description of the local dynamics can be given, while at the same time it remains tractable to analysis. This makes it applicable to a wide range of biological scenarios reaching from the evolution of viral genomes to the evolution of cooperation and altruism. The evolution of ecosystem processes, such as nutrient recycling in plant-detrivore systems and the evolution of social behaviour in aphids, are other possible applications of this theory.
2. Spatio-temporal population dynamics
The importance of spatial interactions for the persistence of these populations is increasingly recognised in both empirical and theoretical work in ecology and epidemiology. A key factor in this is the amount of synchrony in populations. If populations fluctuate in synchrony they are far more likely to become extinct over their entire habitat. On the contrary, if fluctuations occur asynchronously they will average out over the population as a whole. Despite the interest in the dynamics of spatially extended systems, few good methods exist to analyse spatial data. In most cases statistical analysis is done on the aggregates of the spatial data, like the spatial averages or spatial variance. In these analyses much of the information about the spatial dynamics is lost and they seem inadequate to fully characterise spatiotemporal dynamics. I am developing a statistical method to analyse spatial data.
3. The population biology and evolution of viruses and phages
At present, most models for the evolution of viruses, such as HIV, concentrate on the evolution in a single host. By combining an explicit description of the population biology of different strains of the virus within a host and a description of the acquisitions of new hosts through infection we hope to capture the two selective forces that drive the evolution of viruses. I hope to gain insights into the processes that shape the genome and characteristics of a virus, in particular its virulence and its competitiveness towards other strains.
4. The epidemiology of infectous diseases
I am interested in various aspects of epidemiology of infectious diseases and have worked on the epidemiology of measles and of meningococcal disease. I am currently involved in an BBSRC funded to model the effect of diseases on pollinators.
5. Systems biology
We are trying to understand the molecular biology of the invasion of Salmonella enterica in cells, by linking models to data that are generated through an ERASYSBIO+ funded project.
Current Projects:
1. Evolution in structured environments
The modelling framework used in Jansen and Mulder (1999), Bonsall et al. (2004) and Jansen and Vitalis (2007) can be generalised to study evolution in patchy environments for a very large class of local dynamics. The model combines within patch dynamics with dispersal between patches which allows for kin or group selection to occur. This model differs from other models for kin selection in that a realistic description of the local dynamics can be given, while at the same time it remains tractable to analysis. This makes it applicable to a wide range of biological scenarios reaching from the evolution of viral genomes to the evolution of cooperation and altruism. The evolution of ecosystem processes, such as nutrient recycling in plant-detrivore systems and the evolution of social behaviour in aphids, are other possible applications of this theory.
2. Spatio-temporal population dynamics
The importance of spatial interactions for the persistence of these populations is increasingly recognised in both empirical and theoretical work in ecology and epidemiology. A key factor in this is the amount of synchrony in populations. If populations fluctuate in synchrony they are far more likely to become extinct over their entire habitat. On the contrary, if fluctuations occur asynchronously they will average out over the population as a whole. Despite the interest in the dynamics of spatially extended systems, few good methods exist to analyse spatial data. In most cases statistical analysis is done on the aggregates of the spatial data, like the spatial averages or spatial variance. In these analyses much of the information about the spatial dynamics is lost and they seem inadequate to fully characterise spatiotemporal dynamics. I am developing a statistical method to analyse spatial data.
3. The population biology and evolution of viruses and phages
At present, most models for the evolution of viruses, such as HIV, concentrate on the evolution in a single host. By combining an explicit description of the population biology of different strains of the virus within a host and a description of the acquisitions of new hosts through infection we hope to capture the two selective forces that drive the evolution of viruses. I hope to gain insights into the processes that shape the genome and characteristics of a virus, in particular its virulence and its competitiveness towards other strains.
4. The epidemiology of infectous diseases
I am interested in various aspects of epidemiology of infectious diseases and have worked on the epidemiology of measles and of meningococcal disease. I am currently involved in an BBSRC funded to model the effect of diseases on pollinators.
5. Systems biology
We are trying to understand the molecular biology of the invasion of Salmonella enterica in cells, by linking models to data that are generated through an ERASYSBIO+ funded project.