Mapping of the JDL data fusion model to bioinformatics

Information fusion (IF) is a rapidly developing research area which concerns the study of methods to combine the analysis of different data sources in such a way that it increases our understanding of the system under study. The synergistic effects of using multiple data sources and repeatedly updating the model when new data is available, increases the reliability of the model and makes it better suited for e.g. decision support. However, information fusion is a challenging task and more research is needed on how to best integrate data of heterogeneous types and structures in a combined analysis. Initially, IF was mainly used in military contexts, but the algorithms developed are likely to be useful in many other domains. The JDL Data Fusion Model was developed to facilitate IF processes. Here, we investigate its applicability for bioinformatics problems in general and we present an example where it is applied in a study of stem cell differentiation.