Metabolic engineering, proteomics, and metabolomics scientists at the Joint BioEnergy Institute. Shown (l-r) are Taek Soon Lee, Christopher Petzold, Jorge Alonso-Gutierrez, Edward Baidoo, George Wang, and Kevin George. (Credit: Irina Silva/JBEI, Berkeley Lab)

Metabolic engineering, proteomics, and metabolomics scientists at the Joint BioEnergy Institute. Shown (l-r) are Taek Soon Lee, Christopher Petzold, Jorge Alonso-Gutierrez, Edward Baidoo, George Wang, and Kevin George. (Credit: Irina Silva/JBEI, Berkeley Lab)

The development of omics technologies, such as metabolomics and proteomics, and systems biology have dramatically enhanced the ability to understand biological phenomena. However, the interpretation of large omics data and the understanding of complex metabolic interactions in engineered microbes remains challenging.

A new open-source workflow developed by researchers at the Department of Energy’s Joint BioEnergy Institute (JBEI) can help by integrating various omics data and genome-scale models to study the effects of biofuel production in a microbial host.

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