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Genomic Science Program

Systems Biology for Energy and the Environment

Department of Energy Office of Science. Click to visit main DOE SC site.

Genomic Science Program

Science Focus Area: Lawrence Berkeley National Laboratory (LBNL)

ENIGMA (Ecosystems and Networks Integrated with Genes and Molecular Assemblies)

  • Principal Investigator: Paul D. Adams1,2
  • SFA Technical Co-Manager: Adam P. Arkin1,2
  • Lead SFA Element Investigators: Eric J. Alm3, Nitin S. Baliga4, Adam M. Deutschbauer1, Matthew W. Fields5, Terry C. Hazen6,7, Trent R. Northen1, Judy D. Wall8
  • Participating Scientists: Michael W. Adams9, Manfred Auer1, Kelly Bender10, Steven Brenner1,2, Gareth Butland1, Romy Chakraborty1, John-Marc Chandonia1, Inna Dubchak1, Dwayne Elias7, Aindrila Mukhopadhyay1, Anup K. Singh11, Gary E. Siuzdak12, David A. Stahl13, Peter J. Walian1, Jizhong Zhou14
  • Participating Institutions: 1Lawrence Berkeley National Laboratory; 2University of California at Berkeley; 3Massachussetts Institute of Technology; 4Institute for Systems Biology; 5Montana State University, Bozeman; 6University of Tennessee; 7Oak Ridge National Laboratory; 8University of Missouri, Columbia; 9University of Georgia, Athens; 10Southern Illinois University; 11Sandia National Laboratories, Livermore, CA; 12Scripps Research Institute; 13University of Washington; 14University of Oklahoma.
  • Website:
  • KBase App: ENIGMA: Building a reference-based metagenomics workflow in KBase

The goal of the LBNL Genomic Science Program Science Focus Area (SFA), also referred to as ENIGMA (Ecosystems and Networks Integrated with Genes and Molecular Assemblies) is to understand the mechanisms driving the subcellular, cellular, and intercellular networks of microbes that in turn drive macroscopic biogeochemical processes, extending this understanding to the larger framework of microbial communities and ecosystems relevant to DOE missions. To this end, the SFA develops and applies novel platforms for high resolution/high throughput metagenomics, genetics, transcriptomics, proteomics, metabolomics and structural biology approaches to examine the systems biology underlying microbial ecosystems and rapidly advance environmental microbes performing key processes of interest to model-organism status. Guided by studies of microbial consortia and in situ environmental research, single-organism molecular data will be extended across increasingly complex microbial communities to determine the means by which these networks transform environmental signals to behaviors and to link laboratory results to the measurements from field studies. The SFA enables multi-scale studies through the development of a sophisticated computational framework for storage, analysis, visualization and modeling of these data. The ultimate goal of the SFA is to develop new frameworks for collecting and quantitatively analyzing multi-scale information—from molecules to organisms, from cells to communities, and from communities to ecosystems.

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