Elucidating human ageing-related phenotypic abnormalities with a novel hierarchical feature selection-based knowledge discovery framework

Ageing is a complex biological process involving multiple genes that are also related to phenotypic abnormalities. However, the micro view of the associations between ageing and human phenotypic abnormalities is still under-studied. We propose a new hierarchical feature selection method namely HIP+, which selects positive hierarchical information-preserving features according to pre-defined hierarchical ontology information. The experimental results confirm that HIP+ obtained better performance than the state-of-the-art hierarchical feature selection method in predicting human phenotypic abnormalities annotations. We further propose a HIP+-based knowledge discovery framework that also successfully highlights some important associations between biological processes and human phenotypic abnormalities.