A new hybrid self-organizing map and fuzzy logic data mining approach for understanding macrophage signaling pathways through DNA microarray data

Understanding the response of human white blood cells (macrophages) to pathogens may provide insights to both the mechanisms of host defenses and the tactics used by pathogens to circumvent these defenses. The DNA microarray method has evolved to become one of the most powerful tools to understand the dynamics of gene response. Currently there is no standard approach to systematically analyze the data and the interpretation of results can vary dramatically. In this paper, we employed a new hybrid Self-Organizing Map (SOM) and Fuzzy Logic data mining approach to explore patterns of time sequence data from eight bacteria with 977 gene responses that showed significant changes on a microarray chip. We annotated the genes by their "biological processes" of Gene Ontology (GO). Our result suggests that the SOM-Fuzzy logic data mining approach is effective in exploring how human macrophages respond to each bacterium with a unique combination of shared biological processes. The shared processes include: signal transduction, transcription, metabolism, and cell cycle and proliferation. Our result also suggests that there are similar responses (identical genes) to several bacteria and the similarities may be related to the shared mechanism of bacterial pathogenesis.