In silico discoveries for biomedical sciences

Haagen, H. van (2011)

Doctoral Thesis

Text-mining is a challenging field of research initially meant for reading large text collections with a computer. Text-mining is useful in summarizing text, searching for the informative documents, and most important to do knowledge discovery. Knowledge discovery is the main subject of this thesis. The hypothesis that knowledge discovery is possible started with the work done by Swanson. He made, as a first finding, links between Raynaud__s disease and fish oil using intermediate medical terms to relate them to each other. This principle was formalized in the AB- C concept. A and C are not directly related to each other but via an intermediate concept B that needs to be discovered. Tex data can be extended by adding other non textual data such as microarray experiments. Then we are in the field of data-mining. The final goal is to do all kinds of discoveries with computer (in silico) using data sources in order to assist biology research to save time and discover more.

• Text-mining
• ROC curve analysis
• Protein-protein interaction
• Prediction
• Knowledge discovery
• Data-mining

• All authors: Haagen, H. van
• Supervisor: Dunnen, J.T. den
• Co-supervisor: Mons, B.; Hoen, P.A.C. 't; Schuemie, M.J.
• Qualification: Doctor (dr.)
• Awarding Institution: Leiden University Medical Center (LUMC), Leiden University
• Date: 2011-09-21
• ISBN (print): 9789081767606
• Sponsorship: NBIC