NEOANEMIA: a knowledge-based system emulating diagnostic reasoning
Computers and Biomedical Research
Orange: from experimental machine learning to interactive data mining
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
Guest Editorial: Current methodologies for translational bioinformatics
Journal of Biomedical Informatics
ICCBR'10 Proceedings of the 18th international conference on Case-Based Reasoning Research and Development
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In this paper we propose a novel approach to the design and implementation of knowledge-based decision support systems for translational research, specifically tailored to the analysis and interpretation of data from high-throughput experiments. Our approach is based on a general epistemological model of the scientific discovery process that provides a well-founded framework for integrating experimental data with preexisting knowledge and with automated inference tools. In order to demonstrate the usefulness and power of the proposed framework, we present its application to Genome-Wide Association Studies, and we use it to reproduce a portion of the initial analysis performed on the well-known WTCCC dataset. Finally, we describe a computational system we are developing, aimed at assisting translational research. The system, based on the proposed model, will be able to automatically plan and perform knowledge discovery steps, to keep track of the inferences performed, and to explain the obtained results.