Artificial Immune Systems
Programme
- 9:30-10:15
York
Immune Systems and Computation: An interdisciplinary
Adventure Artificial Immune Systems (AIS) is a diverse area of
research that attempts to bridge the divide between immunology and
engineering and are developed through the application of techniques
such as mathematical and computational modeling of immunology,
abstraction from those models into algorithm (and system) design and
implementation in the context of engineering. Whilst AIS has become
known as an area of computer science and engineering that uses immune
system metaphors for the creation of novel solutions to problems, we
argue that the area of AIS is much wider and is not confined to the
simple development of new algorithms. In this talk we would like to
broaden the understanding of what AIS are all about, thus driving the
area into a true interdis- ciplinary one of genuine interaction
between immunology, mathematics and engineering.
- 10:15 -11:00
Kent
Theoretical results on artificial immune systems
Artificial immune systems are a relatively new area of bio-inspired
computation. The inspiration for artificial immune algorithms has
come from biological models of the natural immune system, especially
the theories of clonal selection, immune networks and negative
selection. Moreover, these algorithms have been successfully employed
in a variety of different application areas. However, until quite
recently their has been a dearth of theoretical studies to justify
their use. In this talk, the existing theoretical work on artificial
immune systems is reviewed, and some of the future challenges in this
area are highlighted.
- 11:00-11:30 coffee(level 9)
- 11:30 -12:15
Nottingham
AIS applications
This talk will cover various applications of AIS from their IS
inspiration to their computational implementation. I will point out
what in my opinion has worked well and what hasn't. I will probably
cover 5-6 different applications, one of them in greater detail to
give an idea how we do it (using artificial Dendritic Cells for
Anomaly detection - based on Matzinger's Danger Theory).
- 12:15 -12:45
York
Simulating biology: Towards understanding what the simulation shows
When building simulations of complex systems the task of validation is often overlooked. Validation helps provide confidence in the simulation by exploring the link between the models that we build and the real complex system. In this talk I will highlight how software engineering validation techniques can be used on complex systems. I provide an example of a simulation of lymphocytes migrating from high-endothelial venules into lymph nodes through the walls of the blood vessel. This example suggests that explicitly stating the modelling and simulation assumptions is key to the process of validating the simulation.
- 12:45 -1:15
York
Modelling the Tunability of Early T Cell Signalling Events
The Tunable Activation Threshold hypothesis of T Cells is investigated through computational modelling of T cell signalling pathways
which may contribute towards tuning. Modelling techniques involving the pi-calculus and use of the PRISM model checker are presented,
then applied to produce a stochastic model of T cell signalling. Finally we present initial results from analysis of the model.
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