KBase: the United States department of energy systems biology knowledgebase
Adam Arkin et al.  2018.  Nature Biotechnology.

Over the past two decades, the scale and complexity of genomics technologies and data have advanced from sequencing genomes of a few organisms to generating metagenomes, genome variation, gene expression, metabolites, and phenotype data for thousands of organisms and their communities. A major challenge in this data-rich age of biology is integrating heterogeneous and distributed data into predictive models of biological function, ranging from a single gene to entire organisms and their ecologies. The US Department of Energy (DOE) has invested substantially in efforts to understand the complex interplay between biological and abiotic processes that influence soil, water, and environmental dynamics of our biosphere. The community that has grown around these efforts recognizes the need for scientists of diverse backgrounds to have access to sophisticated computational tools that enable them to analyze complex and heterogeneous data sets and integrate their data and results effectively with the work of others. In this way, new data and conclusions can be rapidly propagated across existing, related analyses and easily discovered by the community for evaluation and comparison with previous results