GraphConnect – Presentation

During the past couple of years, Big Data (analytics) has experienced increasing uptake within various application domains such as government, marketing and finance. But perhaps, the area which has the most to gain is the healthcare sector, where the benefits of efficiently assembling and analysing large quantities of data can literally be life-altering for a countless number of people. This talk will illustrate the power and flexibility of Graph Databases and Neo4J specifically to help in the overall analysis of biological data sets. We will show how to build a visual exploration environment that helps researchers at identifying clusters within various biological data sets, including gene expression and mutation prevalence data. Additionally, we will introduce FluxGraph, a temporal Graph Database that can help researchers at gathering the required insights from a set of longitudinal medical records. By introducing a temporal notion within Graph Databases, researchers are given the power to query beyond time boundaries and get historical access to individual patient characteristics or combinations thereof.