Structures and Relations of Knowledge Nodes: Exploring a Knowledge Network of Disease from Precision Medicine Research Publications.

The vast amount of DNA sequence and protein data are being explored and linked to diseases as causative factors to support clinical and healthcare decision making. These developments in data-intensive biological sciences and clinical practices raised new questions for knowledge organization systems (KOS), and taxonomies in particular. Sitting at the center of these questions is the lagging of KOS’s capabilities in responding to the rapidly changing and emerging biomedical and disease terms due to the static, hierarchical structures and disconnection with new disease data fin traditional KOSs. This paper reports a pilot study that is designed to uncover and identify the types of knowledge nodes and relationships that can help generalize a framework or model for building a Knowledge Network of Disease, or the New Taxonomy envisaged by the
National Academy of Science. This pilot study examined a sample of biomedical
publications and drew a knowledge map to lay out the main knowledge nodes and their relationships. A preliminary framework for constructing the Knowledge Network of Disease is discussed.