Abstract

The complex variation of microbial communities presents a rich source of inspiration and challenges for computational analysis. This talk will consider the role of ecological memory and interactions in shaping up the dynamical landscape of community stability and resilience. Moreover, we will highlight common limitations in human microbiome studies, where the availability of longitudinal time series and the possibilities for controlled experimental replication are often remarkably limited. Incorporating prior knowledge and combining evidence across multiple sources can help to overcome some of the limitations in data availability, enhance prediction accuracy, and provide a more holistic view of the dynamical system. The talk will conclude by introducing a new open source framework for the integration and analysis of longitudinal microbiome data.