Data fusion and analysis tools to enable machine learning for systems biology and bioenergy

Sustainable production systems for biofuels and bioproducts require knowledge about the interplay between crop selection, environment, management and key plant-microbe- environment interactions. This knowledge is contained in complex multimodal inter-related datasets which contain complementary information about biofuel crops. However, there is a lack of tools which can effectively fuse and analyze such multimodal datasets to address biological questions. Subsurface Insights will develop tools for multimodal biofuel data fusion and analysis. The tools will be open source. In Phase I we will develop an initial version of these tools and demonstrate their capability using data from a DOE funded poplar research study in Mississippi This tool will support the US biofuel industry in selecting optimal cultivars given site conditions. The same technology can also be used to optimize selection of other crops for the agricultural industry at large.