High throughput data analysis is a challenging problem due to the vast amount of available data. A major concern is to develop algorithms that provide accurate numerical predictions and biologically relevant results. A wide variety of tools exist in the literature using biological knowledge to evaluate analysis results. Only recently, some works have included biological knowledge inside the analysis process improving the prediction results.
Bosio, M., Salembier, P., Bellot, P., Oliveras, A. Hierarchical clustering combining numerical and biological similarities for gene expression data classification. A: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. "Conference proceedings : 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference". Osaka: Institute of Electrical and Electronics Engineers (IEEE), 2013, p. 584-587.