Integration of Clinical and Gene Expression Data Has a Synergetic Effect on Predicting Breast Cancer Outcome

Breast cancer outcome can be predicted using models derived from gene expression data or clinical data. Only a few studies have created a single prediction model using both gene expression and clinical data. These studies often remain inconclusive regarding an obtained improvement in prediction performance. We rigorously compare three different...

Knowledge driven decomposition of tumor expression profiles

A comprehensive analysis of prognostic signatures reveals the high predictive capacity of the Proliferation, Immune response and RNA splicing modules in breast cancer

Pooling breast cancer datasets has a synergetic effect on classification performance and improves signature stability

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Module-Based Outcome Prediction Using Breast Cancer Compendia

Background. The availability of large collections of microarray datasets (compendia), or knowledge about grouping of genes into pathways (gene sets), is typically not exploited when training predictors of disease outcome. These can be useful since a compendium increases the number of samples, while gene sets reduce the size of the feature space....