Genomic Science Program Systems Biology for Energy and Environment

Genomic Science Program Systems Biology for Energy and Environment

Encoded in the genomes of plants, microbes, and their communities are principles that offer a wealth of potential for biobased solutions to national energy and environmental challenges. To harness this potential, the U.S. Department of Energy’s Genomic Science program supports fundamental research to understand the systems biology of plants and microbes as they respond to and modify their environment. This research builds on the foundation of sequenced genomes and metagenomes, focusing on a tightly coupled approach that combines experimental physiology, omics-driven analytical techniques, and computational modeling of functional biological networks.
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Miscanthus (GLBRC)

Advances basic research to underpin production of biofuels and bioproducts from inedible lignocellulosic plant biomass.
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E Coli (JBEI)

Improves fundamental understanding of microbes with bioenergy-relevant traits for deconstructing biomass and synthesizing biofuels and bioproducts.
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Biofeedstock (CABBI)

Elucidates and validates the functional roles of genes, gene families, and associated pathways to enhance understanding of critical processes in DOE-relevant plant systems.
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C thermocellum (ORNL)

Investigates plant-soil-microbe interactions in laboratory and field settings to enhance biomass productivity under changing biotic and abiotic conditions.
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C zofingiensis starch

Develops knowledge for engineering useful traits into plants and microbes to produce biofuels and bioproducts and to advance biotechnology.
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Permafrost Microbes (EMSL)

Links structure and function of microbial communities in the field with key environmental or ecosystem processes.
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Kalanchoe gene map (ORNL)

Provides new computational approaches and hypothesis-generating analysis techniques, data, and simulation capabilities such as the DOE Systems Biology Knowledgebase (KBase) to accelerate collaborative, reproducible systems science.
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kbase logo

Community-driven cyberinfrastructure for sharing and integrating data and analytical tools to accelerate predictive biology.
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Penicillium spores using SEM (EMSL)

Empowering an international community of scientists with the most advanced technologies.
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Publication Highlights


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