Who am I and what am I doing here?

1. Who am I and what am I doing here? Allan Tucker A brief introduction to my research www.brunel.ac.uk\~cssrajt

2. Outline of talk • My background • My current research and collaborations • A sample of results and publications • Plan of future research and funding • Conclusions

3. A bit of background • BSc Cognitive Science: University of Sheffield, 1996 • PhD Computer Science: University of London, 2001 • Post doctorate research: Brunel University, 2001-2004

4. IDA group at Brunel • Headed by Professor Liu • Bioinformatics, Genomics, and Medical Informatics • Data Mining and Intelligent Systems • Dynamic Systems and Signal Processing • Graphics, Images and Visualisation • Multivariate Time Series and Statistical Analysis

5. Areas of interest • Bayesian networks • Automatic explanation of data • Multivariate time series • Classification • Optimisation

6. Collaborations • Moorfield’s eye hospital • Visual field understanding and classification • UCL, Department of virology • Gene expression data • Royal Holloway • Optimisation • Brunel University • Within IDA • Software engineering

7. One slide tutorial on Bayesian networks • Graph structure • Local probability distributions • Combine expert knowledge and data (but little research on this)

8. Some results • Spatio-temporal models of visual fields • Artificial intelligence in medicine, 2004

9. Some results (continued) • Predicting Glaucoma

10. Some results (continued) • Explanation • Intelligent Data Analysis, 2002 & 2004

11. Some results (continued) • Combining expert knowledge and data to identify relevant genes • Bioinformatics, under review

12. Journal Publications • Tucker, A. Crampton, J. Swift, S. “RGFGA: An Efficient Representation and Crossover for Grouping Genetic Algorithms” Evolutionary Computation, Provisionally Accepted. • Tucker, A. Vinciotti, V. Liu, X. Garway-Heath, D. “A Spatio-Temporal Bayesian Network Classifier for Understanding Visual Field Deterioration”, Artificial Intelligence in Medicine, Elsevier, In Press. • Swift, S. Tucker, A. Liu, X. Martin, N. Orengo, C. Kellam, P. “Consensus Clustering and Functional Interpretation of Gene Expression Data”, Genome Biology, In Press. • Tucker, A. Vinciotti, V. Liu, X. “The Robust Selection of Predictive Genes Via a Simple Classier”, Submitted to Bioinformatics. • Tucker, A and Liu, X “A Bayesian Network Approach to Explaining Time Series with Changing Structure”, Intelligent Data Analysis – An International Journal, In Press. • Kellam, P. Liu, X. Martin, N. Orengo, C. Swift, S. Tucker, A. “A Framework for Modelling Virus Gene Expression Data”, Intelligent Data Analysis, 2002. • Counsell, S. Liu, X. Mcfall, J. Swift, S. Tucker, A “Using Evolutionary Computation for Clustering Email Data”, Intelligent Data Analysis, 2002. • Tucker, A. Liu, X. Ogden-Swift, A. “Evolutionary learning of dynamic probabilistic models with large time lags”, International Journal of Intelligent Systems, 2001. • Swift, S. Tucker, A. Martin, N. Liu X. “Grouping Multivariate Time Series Variables: Applications to Chemical process and Visual Field Data”, Knowledge Based Systems, 2001. • Tucker, A. Swift, S. Liu, X. “Grouping Multivariate Time Series via Correlation”, IEEE Transactions on Systems, Man, and Cybernetics. Part B: Cybernetics, 2001.

13. Recent Conference Publications • Vinciotti, V. Tucker, A. Liu, X. Panteris, E. Kellam, P. “Identifying genes with high confidence from small samples”, Workshop on Data Mining in Functional Genomics, at the European Conference in Artificial Intelligence ECAI 2004. • Sheng, W. Tucker, A. Liu, X. “Clustering with Niching Genetic K-means Algorithm”, GECCO 2004. • Tucker, A. Vinciotti, V. Liu, X. Garway-Heath, D. “Bayesian Networks to Classify Visual Field Data”, The Association for Research in Vision and Ophthalmology Annual Conference, ARVO 2004. • Tucker, A. Garway-Heath, D. Liu, X. “Bayesian Classification and Forecasting of Visual Field Deterioration”, Proceedings of IDAMAP 2003. • Counsell, S., Liu, X., Najjar, R., Swift, S., Tucker, A., “Applying Intelligent Data Analysis to Coupling Relationships in Object-oriented Software”, IDA 2003. • Tucker, A. Liu, X. “Learning Dynamic Bayesian Networks from Multivariate Time Series with Changing Dependencies”, IDA 2003. • Tucker, A. Garway-Heath, D. Liu, X. “Spatial Operators for Evolving Dynamic Probabilistic Networks from Spatio-Temporal Data”, GECCO 2003. • Counsell, S. Liu, X. McFall, J. Swift, S. and Tucker, A. “Optimising the Grouping of Email Users to Serves Using Intelligent Data Analysis”, ICEIS 2001. • Kellam, P. Liu, X. Martin, N. Orengo, C. Swift, S. Tucker, A. “A Framework for Modelling Short, High-Dimensional Multivariate Time Series: Preliminary Results in Virus Gene Expression Data Analysis”, IDA 2001. • Tucker, A. Swift, S. Martin, N. Liu X. “Grouping Multivariate Time Series Variables: Applications to Chemical process and Visual Field Data”, ES 2000.

14. Future directions • Continue existing research collaborations • Bioinformatics – HIV data, Gene identification • Software Engineering – Analysis of code • Optimisation – adaptive parameters, representations • Recently secured funding from Zeis Meditech in conjunction with Moorfield’s to generate substantial data on visual fields and retinal images • EPSRC first grant • Optimisation with adaptive parameters • BBSRC new investigation scheme • Combining databases (GO ENSEMBL) into coherent models of the human genome • EPSRC advanced fellowship?

15. Summary • Record of working within Brunel over 4 years • Multiple projects and collaborations with a number of institutions • Good publication record including several “grade A” journals • Keen to build upon my research record

16. Thanks for listening Any questions?

17. Some results • Clustering (MTS and Consensus) • IEEE System Man & Cybernetics, 2001 • Genome Biology, 2004

18. Some results (continued) • Efficient representations for GAs • International Journal of Intelligent Systems, 2001 • Evolutionary computation, provisionally accepted