KEYNOTES

1. Professor Derek Smith

The Evolution of Influenza Viruses

Thirty plus years of global influenza virus surveillance, in multiple species, provides a remarkable dataset for the study of influenza virus evolution. Because the purpose of much of this surveillance is vaccine strain selection, these data have been analyzed antigenically as well as genetically. I will describe the evolution of the current A(H1N1) influenza pandemic, of seasonal influenza A(H3N2) viruses from the last influenza pandemic in 1968, and of ~13,000 influenza A(H3N2) viruses from six continents during 2002-2007. One finding of these studies is that from 2002-2007, A(H3N2) influenza viruses did not persist in any individual country, but nevertheless continuouly circulated in East and Southeast Asia (E-SE Asia) via a region-wide network of temporally overlapping epidemics. Seasonal A(H3N2) epidemics in the rest of the world were seeded from this E-SE Asian network each year. If the trends observed during this period are an accurate representation of overall patterns of spread, then the evolution, and thus antigenic characteristics, of A(H3N2) viruses outside E-SE Asia may be forecast each year based on surveillance within E-SE Asia. These studies of human influenza viruses will be constasted with studies in other species, to show the importance of the coevolution of the virus and population-level immunity to the virus.

Derek Smith is Professor of Infectious Disease Informatics in the Zoology Department at Cambridge University. He is also a member of the Department of Virology at Erasmus Medical Center in The Netherlands, and is a Senior Research Fellow at the Fogarty International Center at the United States National Institutes of Health. He is an advisor to the World Health Organization and is a member of its influenza vaccine strain selection committee and is also involved in vaccine strain selection for other human and non-human pathogens. His research is focused on how pathogens evolve, to what extent this evolution is predictable, and determining public and animal health measures against such ever-changing pathogens. He received a United States National Institutes of Health Director's Pioneer Award in 2005 for his work on Antigenic Cartography, a method that enables detailed study of pathogen evolution.

2. PD Dr.-Ing Falko Dressler

Self-Organization in Sensor Networks based on Biological Concepts

The turn to nature has brought us many unforeseen great concepts and solutions. This course seems to hold on for many technical research domains. In this talk, I want to focus on the behavior and the challenges in networked embedded systems with primary focus on wireless ad hoc and sensor networks, which are meant to self-organize in large groups of nodes. The existing bio-inspired networking and communication protocols and algorithms devised by looking at biology as a source of inspiration, and by mimicking the laws and dynamics governing these systems is presented along with open research issues for the bio-inspired networking. The objective is to provide better understanding of the potentials for bio-inspired and nano-scale networking, and to motivate the research community to further explore this timely and exciting field. Based on selected research activities in the field of sensor and actor networks, I will show the capabilities of such bio-inspired solutions even though some are not yet fully understood and evaluated. In particular, I will highlight a programming and information processing scheme for heterogeneous sensor systems inspired by cellular signaling networks as well as some combined task allocation and routing approach for mobile robots interacting with a sensor network.

Falko Dressler is an assistant professor coordinating the Autonomic Networking Group at the Department of Computer Sciences, University of Erlangen. He teaches on self-organizing sensor and actor networks, network security, and communication systems. Dr. Dressler received his M.Sc. and Ph.D. degree from the Dept. of Computer Sciences, University of Erlangen in 1998 and 2003, respectively. Dr. Dressler is an editor for Elsevier Ad Hoc Networks, ACM/Springer Wireless Networks (WINET), and the new Elsevier Nano Communication Networks journal. He served as guest editor of special issues on self-organization, autonomic networking, and bio-inspired computing and communication for IEEE Journal on Selected Areas in Communications (JSAC), Elsevier Ad Hoc Networks, and Springer Transactions on Computational Systems Biology (TCSB). Dr. Dressler was general chair of the 2nd IEEE/ACM International Conference on Bio-Inspired Models of Network, Information, and Computing Systems (BIONETICS 2007). Dr. Dressler published two books including Self-Organization in Sensor and Actor Networks, published by Wiley in 2007. Dr. Dressler is Senior Member of the IEEE as well as of the ACM. His research activities are focused on (but not limited to) Autonomic Networking addressing issues in Wireless Ad Hoc and Sensor Networks, Vehicular Communication, Self-Organization, Bio-inspired Mechanisms, and Adaptive Network Monitoring and Security Techniques.

3. Dr. rer. nat Serge Kernbach

Multicellular Self-Adaptation and Self-Development: new paradigm for collective adaptive systems?

Self-adaptation and self-development represent key features of adaptive systems, targeting a long-term autonomy and sustainability in real environments. Collective systems, such as networked and swarm robotics, ubiquitous and cloud computing, sensing and actuation networks possess a great developmental plasticity, which is required for achieving extended adaptability. Current trend in collective adaptive systems is related to a transition from networks of independent elements to symbiotically-organized multicellular organisms with such sources of bio-inspiration as morpho- and embryogenesis, immunology and reproduction, controllable-emergent phenomena and long-term evolution. Multicellular self-adaptation and self-development create new research challenges and new technological perspectives for the next generation of adaptive systems. This talk is intended to give an overview about collective adaptive systems in robotics, to introduce concepts of artificial multicellularity and to discuss self-* features of such systems.

TUTORIALS

1. Mathematical Modelling for Immunology

Dr Hugo Van den Berg, University of Warwick

Biography
Hugo van den Berg graduated cum laude from the Free University in Amsterdam in 1992, earning an MSc in theoretical neuroscience. In 1998 he obtained a PhD at the same University in theoretical population biology and became a Research Fellow at the University of Warwick, where he started working on the specificity of T cell receptors. His other research interests include myometrial activity patterns and whole-body energetics.

2. Agent-based modelling of biological systems: from cells to tissue

Mike Holcombe, The University of Sheffield

Abstract
We will look at new techniques for simulating complex systems using agent-based models and supercomputers. The FLAME (Flexible Large-scale Agent-based Modelling Environment) has been developed following rigorous software engineering best practice to provide an environment where researchers can build highly detailed and robust models. FLAME is a program generator that starts with a specification of all the different agent types in a Multi-agent system and directly produces a highly optimised C program that will run on any computer system - desktop, Grid, parallel supercomputer etc. It is also available for GPGPUs for graphics-intensive applications. The basis of FLAME is a fully general computational model and thus it is applicable to many situations in biology, medicine, economics and social systems, for example. FLMAE can be integrated with other applications and solvers, for example COPASI used in mathematical and systems biology (it is SBML compliant). We will look at how to engineer massive agent-based systems using FLAME and the associated techniques for model testing, model validation and verification. techniques for automatically discovering emergent phenomena from massive data sets produced by these simulations will also be mentioned. Examples will be drawn from: models of the innate immune system in mammallian cells, models of the molecular basis for oxygen processing in E. coli and the development and repair of epithelial tissue.

3. Insights into working with AIS in industry

Dr Mark Neal, University of Wales, Aberystwyth

Abstract
Research council funding and European projects tend to be the bread and butter of academics' research income, but pressure to contribute to the "third mission" of university activity is pushing academics towards work more with industrial partners. Whilst I do not claim to be an industry expert, I have now had dealings with a number of companies and projects in this area and there are some positive lessons to be learnt. This session will explain the benefits that I perceive when working on industry-driven projects and I will attempt to clarify what the companies that I have dealt with have expected from me. The session will also outline some of the negative aspects and address some ways to guard against them. In particular I will address the often surprisingly realistic expectations and sensible approaches that companies have when working with academics. On the negative side I will outline my somewhat time-consuming approach to making the most of industry contacts and the occasionally sadistic tendencies of contract lawyers on both the academic and industrial sides.