16. Phylogenetic Cladograms: Tools for Analyzing Biomedical Data

This chapter provides an introduction to phylogenetic cladograms – a systems biology evolutionary-based computational methodology that emphasizes the importance of considering multilevel heterogeneity in living systems when mining data related to these systems. We start by defining intelligence as the ability to predict, because prediction is a very important objective in mining data, especially biomedical data (Sect. 16.1). We then give a brief review of artificial intelligence (AI) and computational intelligence (CI) (Sects. 16.2, 16.3), provide a conciliatory overview of CI, and suggest that phylogenetic cladograms which provide hypotheses about speciation and inheritance relationships should be considered to be a CI methodology. We then discuss heterogeneity in biomedical data and talk about data types, how statistical methods blur heterogeneity, and the different results obtained between more traditional CI methodologies (phenetic) and phylogenetic techniques. Finally, we give an example of constructing and interpreting a phylogenetic cladogram tree.