All Outputs (4)

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

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., …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.

Consensus clustering and fuzzy classification for breast cancer prognosis (2010)
Presentation / Conference Contribution
Garibaldi, J. M., Soria, D., & Rasmani, K. A. (2010). Consensus clustering and fuzzy classification for breast cancer prognosis.

A novel framework to elucidate core classes in a dataset (2010)
Presentation / Conference Contribution
Soria, D., & Garibaldi, J. M. (2010). A novel framework to elucidate core classes in a dataset.

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.