| [18] | The DATA Bonanza: Improving Knowledge Discovery for Science, Engineering and Business (MP Atkinson, R Baxter, P Brezany, O Corcho, M Galea, J van Hemert, M Parsons, D Snelling), John Wiley & Sons, 2013.
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| [17] | EnzML: multi-label prediction of enzyme classes using InterPro signatures (L De Ferrari, S Aitken, J van Hemert, I Goryanin), In BMC Bioinformatics, volume 13, 2012.
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| [16] | Performance database: capturing data for optimizing distributed streaming workflows (C Liew, M Atkinson, ..., J van Hemert, L Han), In Philos T R Soc A, volume 369, 2011.
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| [15] | A Generic Parallel Processing Model for Facilitating Data Mining and Integration (L Han, CS Liew, Malcolm PA, JI van Hemert), In Parallel Computing, Elsevier, volume 37, 2011.
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| [14] | Automating Gene Expression Annotation for Mouse Embryo (L Han, MP Atkinson, RA Baldock, J van Hemert), In Advanced Data Mining and Applications, volume 5, 2009.
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| [13] | An E-infrastructure to Support Collaborative Embryo Research (A Barker, J van Hemert, RA Baldock, MP Atkinson), In Cluster Computing and the Grid, IEEE Computer Society, volume 9, 2009.
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| [12] | A distributed architecture for data mining and integration (MP Atkinson, J van Hemert, L Han, A Hume, CS Liew), In Data-Aware Distributed Computing, ACM, volume 2, 2009.
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| [11] | A Novel Visual Discriminator for Network Traffic Patterns (L Han, J van Hemert), In Advanced Engineering Computing and Applications in Sciences, volume 2, 2008.
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| [10] | Matching Spatial Regions with Combinations of Interacting Gene Expression Patterns (J van Hemert, RA Baldock), In BioInformatics Research and Development (M Elloumi, \emphet al., eds.), Springer, volume 2, 2008.
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| [9] | Mining spatial gene expression data for association rules (J van Hemert, RA Baldock), In BioInformatics Research and Development (S Hochreiter, R Wagner, eds.), Springer, volume 4414, 2007.
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| [8] | Application of Evolutionary Computation to Constraint Satisfaction and Data Mining (J van Hemert), PhD thesis, Leiden University, 2002.
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| [7] | Evolutionary Computation in Constraint Satisfaction and Machine Learning --- An abstract of my PhD. (J van Hemert), In Proceedings of the Brussels Evolutionary Algorithms Day (BEAD-2001) (Anne Defaweux, Bernard Manderick, Tom Lenearts, Johan Parent, Piet van Remortel, eds.), Vrije Universiteit Brussel (VUB), 2001.
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| [6] | Adaptive Genetic Programming Applied to New and Existing Simple Regression Problems (J Eggermont, J van Hemert), In Genetic Programming (J Miller, M Tomassini, PL Lanzi, C Ryan, AGB Tettamanzi, WB Langdon, eds.), Springer, 2001.
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| [5] | Stepwise Adaptation of Weights for Symbolic Regression with Genetic Programming (J Eggermont, J van Hemert), In Proceedings of the Twelfth Belgium/Netherlands Conference on Artificial Intelligence (A van den Bosch, H Weigand, eds.), 2000.
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| [4] | Comparing genetic programming variants for data classification (J Eggermont, AE Eiben, J van Hemert), In Proceedings of the Eleventh Belgium/Netherlands Conference on Artificial Intelligence (E Postma, M Gyssens, eds.), 1999.
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| [3] | A comparison of genetic programming variants for data classification (J Eggermont, AE Eiben, J van Hemert), In Advances in Intelligent Data Analysis (DJ Hand, JN Kok, MR Berthold, eds.), Springer, 1999.
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| [2] | Adapting the Fitness Function in GP for Data Mining (J Eggermont, AE Eiben, J van Hemert), In Genetic Programming (R Poli, P Nordin, WB Langdon, TC Fogarty, eds.), Springer, 1999.
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| [1] | Applying Adaptive Evolutionary Algorithms to Hard Problems (J van Hemert), Master's thesis, Leiden University, 1998.
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