Knowledge Discovery in Datasets of Proteomics by Systems Modeling in Translational Research on Pancreatic Cancer.

Knowledge discovery in databases (KDD) can contribute to translational research, also known as translational medicine, by bridging the gap between and studies and clinical applications. Here, we propose a 'systems modeling' workflow for KDD. This framework includes data collection of composition model (various research models) and processing model (proteomics) and analytical model (bioinformatics, artificial intelligence/machine leaning and pattern evaluation), knowledge presentation, and feedback loops for hypothesis generation and validation.