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All Outputs (5)

Learning pathway-based decision rules to classify microarray cancer samples (2010)
Presentation / Conference Contribution
Glaab, E., Garibaldi, J. M., & Krasnogor, N. Learning pathway-based decision rules to classify microarray cancer samples. Presented at 25th German Conference on Bioinformatics 2010

Despite recent advances in DNA chip technology current microarray gene expression studies are still affected by high noise levels, small sample sizes and large numbers of uninformative genes. Combining microarray data with cellular pathway data by us... Read More about Learning pathway-based decision rules to classify microarray cancer samples.

A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients (2010)
Journal Article
Soria, D., Garibaldi, J. M., Ambrogi, F., Green, A. R., Powe, D., Rakha, E., Douglas Macmillan, R., Blamey, R. W., Ball, G., Lisboa, P. J., Etchells, T. A., Boracchi, P., Biganzoli, E. M., & Ellis, I. O. (2010). A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients. Computers in Biology and Medicine, 40(3), https://doi.org/10.1016/j.compbiomed.2010.01.003

Single clustering methods have often been used to elucidate clusters in high dimensional medical data, even though reliance on a single algorithm is known to be problematic. In this paper, we present a methodology to determine a set of ‘core classes’... Read More about A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients.

A novel framework to elucidate core classes in a dataset (2010)
Presentation / Conference Contribution
Soria, D., & Garibaldi, J. M. A novel framework to elucidate core classes in a dataset. Presented at IEEE Congress on Evolutionary Computation (CEC) 2010

In this paper we present an original framework to extract representative groups from a dataset, and we validate it
over a novel case study. The framework specifies the application of different clustering algorithms, then several statistical and visu... Read More about A novel framework to elucidate core classes in a dataset.

Real-world transfer of evolved artificial immune system behaviours between small and large scale robotic platforms (2010)
Journal Article
Whitbrook, A., Aickelin, U., & Garibaldi, J. (2010). Real-world transfer of evolved artificial immune system behaviours between small and large scale robotic platforms. Evolutionary Intelligence, 3(3-4), https://doi.org/10.1007/s12065-010-0039-7

In mobile robotics, a solid test for adaptation is
the ability of a control system to function not only in a
diverse number of physical environments, but also on a
number of different robotic platforms. This paper demonstrates that a set of behavi... Read More about Real-world transfer of evolved artificial immune system behaviours between small and large scale robotic platforms.