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Papers  
Hawkins, J., Mahony, D., Maetschke, S., Wakabayashi, M., Teasdale, R. and Bodén, M. (2007). Identifying Novel Peroxisomal Proteins. Proteins: structure, Function, and Bioinformatics. Volume 69, Issue 3, Pages 606 - 616. View
Hawkins, J., Davis, L. and Bodén, M. (2007). Predicting Nuclear Localization. Journal of Proteome Research. 6(4); 1402-1409. View

Davis, L., Hawkins, J., Maetschke, S. and Bodén, M. (2006). Comparing SVM sequence kernels: A protein subcellular localization theme, In Proceedings of the Workshop on Intelligent Systems for Bioinformatics, CRPIT (vol. 73).

Hawkins, J. and Bodén, M. (2006). Multi-stage Redundancy Reduction: Effective Utilisation of Small Protein Data Sets, In Proceedings of the Workshop on Intelligent Systems for Bioinformatics, CRPIT (vol. 73).

Bodén, M. and Hawkins, J. (2006). Evolving discriminative motifs for recognizing proteins imported to the peroxisome via the PTS2 pathway. CEC 2006, (Winner: Best Paper in Session).
Hawkins, J., Beard, R. and McDonald, S. (2006). A multi-agent simulation model of fishery fleet dynamics for the Queensland coral reef line fishery. AARES 2006
Hawkins, J. and Bodén, M. (2006). Detecting and Sorting Targeting Peptides with Recurrent Networks and Support Vector Machines. Journal of Bioinformatics and Computational Biology, 4(1).
Hawkins, J. and Bodén, M. (2005). Predicting Peroxisomal Proteins. 2005 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology
Watson, J., Hawkins, J., Bradley, D., Dassanayake, D., Wiles, J., and Hanan, J. (2005). Towards a network pattern language for complex systems. In Abbass, H., Bossamaier, T., and Wiles, J., editors, Recent Advances in Artificial Life, Volume 3 of Advances in Natural Computation, Pages 309-317, 349-358. World Scientific.
Bodén, M. and Hawkins, J. (2005) Prediction of subcellular localisation using sequence-biased recurrent networks. Bioinformatics. 21(10), pp. 2279-2286.
Wakabayashi, M., Hawkins, J., Maetschke, S. and Bodén, M. (2005) Exploiting sequence dependencies in the prediction of peroxisomal proteins. In Intelligent Data Engineering and Automated Learning - IDEAL 2005, pp. 454-461.
Hawkins, J. and Bodén, M. (2005). The Applicability of Recurrent Neural Networks for Biological Sequence Analysis. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2(2).
Bodén, M. and Hawkins, J. (2005). Improved access to sequential motifs: A note on the architectural bias of recurrent networks. IEEE Transactions on Neural Networks. 16(2), 491-494.
Bodén, M. and Hawkins, J. (2005). Detecting residues in targeting peptides. In Proceedings of the Asia-Pacific Bioinformatics Conference. Singapore.
Submitted  
Hawkins, J. and Bodén, M., The Janus Face of Bias: Machine Learning Architectures for Biological Motif Recognition
Hawkins, J. and Bailey, Timothy L., The Statistical Power of Phylogenetic Motif Models
In Preparation  
Hawkins, J. and Bodén, M., When Recurrent Networks Fail!
Abandoned  
Hawkins, J. and Bodén, M., Exploring the Architectural Bias of Neural Networks for Biological Sequence Recognition