School of Computing

Computational Intelligence Group

The Group focuses on the intersection between Computer Science, Biology and Psychology. We are interested in how biological and psychological systems can be modelled using computation and how biological systems can inspire new forms of computation. We also examine both how this novel computation and how the application of psychology can be used in practical setttings such as data mining and visualization.

The interdisciplinary nature of the work in the group means that many of the members are active in the Centre for BioMedical Informatics, a university-wide virtual Centre that aims to foster collaborative research and postgraduate teaching in the broad area of Biomedical Informatics.

Our work is consistently published in highly ranked journals, and has been supported by a number of research grants. A full list of the group's papers.

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Modelling Biological Systems

Our interests include modelling biological systems at various levels, which can greatly improve the understanding of such systems. In particular, recent work has concentrated on computational modelling of bacterial Fimbriae which allow bacterial parasites to attach themselves to host cells. We have also, alongside biologists, investigated the computational properties of gene regulatory networks. Gene networks have attracted much recent interest due to the considerable amount of data being made available through new experimental techniques.

Working with the School of Biosciences, we have also developed software to assist in the analysis of NMR relaxation data.

The RPLOT program
The advent of propriety pulse sequences from the major NMR manufacturers has made the acquisition of 15N NMR relaxation data easy, but basic properies can be non-trivial to deduce. The RPLOT program enables the user to easily deduce global correlation time and identify individual 15N nuclei exhibiting Rex line broadening behaviour.

Key Publications:

Recent Research Funding:

Contact: Dominique Chu
Contact: David Barnes

Virtual P3 ERPimages
Virtual P3 ERPimages for targets seen outside and inside the AB
From Attention Increases the Temporal Precision of Conscious Perception

Cognitive Systems

Our research explores how the mind emerges from the brain to generate a spectrum of cognitive capacities. This involves studying perception, consciousness, attention, language, emotions and decision-making using a mixture of methods, including behavioural and electrophysiological (EEG) experimentation and connectionist and symbolic modelling. We also undertake applied neuroscience research focussed on brain-computer and human-computer interfaces.

Key Publications:

Contact: Howard Bowman

Bioinspired Computing

This work finds effective solutions to hard problems by using strategies inspired by biological systems. Examples of bioinspired techniques are evolutionary algorithms, neural networks, swarm intelligence methods and artificial immune systems. We have applied such techniques to data analysis, music technology, pure mathematics, robotics, multimodal optimization, and bioinformatics

We have a particular interest in genetic programming methods where the aim is to create software from descriptions of required functionality rather than by stating exactly what programs should do. We are looking how to combine software engineering and program analysis methods with automatic programming techniques to produce rigorous programs in an automatic fashion. We are also interested in how different soft computing techniques, such as artificial immune systems, can be used for genetic programming.

Key Publications:

Recent Research Funding:

Contact: Colin Johnson

Data Mining and Bioinformatics

We have explored a number of novel approaches to data mining, including evolutionary algorithms, swarm intelligence (mainly ant colony optimization) and new hierarchical classification methods. This work has been applied to knowledge discovery in a number of application areas, particularly protein function prediction, and in the increasingly important area of studying ageing in humans.

Recent Research Funding:

Key Publications:

Contact: Alex Freitas

Information Visualization

eulerAPE for real data sets: Lenz & Fornoni, BMC Medicine 2006
A visualization of medical data with the software eulerAPE.
eulerAPE is the first automatic area-proportional Venn-3 diagram drawing tool that uses ellipses. It draws accurate, readable diagrams for most random data.
Our focus is on ways to make complex information understandable by visual means. The kinds of data we visualize includes networks and Euler diagrams. Current research includes examining the metro map metaphor for visualizing interlinking network diagrams. Allowing access to metro maps on mobile devices, such as smartphones, could improve navigation on public transport networks. Smartphones also have convenient interfaces for uses to create their own diagrams, and we are looking at sketch and gesture input for user input to both schematic maps and Euler diagrams.

Euler diagrams are unique in being able to intuitively represent intersections and containment of sets. They are in common use where visual representations of logic are required, but are also used visualize the outcome of experiments in medicine and biosciences. We have developed novel methods to automatically visualize area proportional Euler diagrams, and have developed the first technology that allows any abstract description to be visualized as an Euler diagram.

Key Publications:

Recent Research Funding:

Contact: Peter Rodgers

School of Computing, University of Kent, Canterbury, Kent, CT2 7NF

Enquiries: +44 (0)1227 824180 or contact us.

Last Updated: 31/03/2017