Genomic Science Program

DOE Systems Biology Knowledgebase for a New Era in Biology

The Genomic Science program’s ultimate goal of achieving a predictive understanding of biological systems is a daunting challenge and will require the integration of immense amounts of diverse information—functional descriptions assigned to DNA sequence, molecular interactions, images of molecules or physical structures within an organism, and details about the environment in which an organism lives. These types of information typically have not been integrated and compared, and the heterogeneous mix of data emanating from the Genomic Science program will span diverse environmental conditions, spatial scales (nanometers to kilometers), and temporal scales (nanoseconds to decades). To address this grand challenge, DOE will develop a Systems Biology Knowledgebase (Kbase) to facilitate a new level of scientific inquiry (see the DOE Systems Biology Knowledgebase brochure PDF).

DOE’s Vision for a Systems Biology Knowledgebase

The DOE Systems Biology Knowledgebase (see figure below) is envisioned as an open cyberinfrastructure to integrate systems biology data, analytical software, and computational modeling tools that will be freely available to the scientific community, the Knowledgebase will drive two classes of work: (1) experimental design and (2) modeling and simulation.

This knowledgebase would facilitate a new level of scientific inquiry by serving as a central component for the integration of modeling, simulation, experimentation, and bioinformatic approaches. Scientists’ ever-increasing exploitation of the dynamic linkages among data integration, experimentation, and modeling and simulation—aided by the Knowledgebase—will advance efforts to achieve a predictive understanding of the functions of biological systems. The Knowledgebase, therefore, must serve multiple roles, including (1) a repository of data and results from high-throughput experiments; (2) a collection of tools to derive new insights through data synthesis, analysis, and comparison; (3) a framework to test scientific understanding; (4) a heuristic capability to improve the value and sophistication of further inquiry; and (5) a foundation for prediction, design, manipulation, and, ultimately, engineering of biological systems to meet national needs in bioenergy, environmental remediation, and carbon cycling.

 

DOE’s Vision for a Systems Biology Knowledgebase. The systems biology research community requires the integration of a wide range of high-volume data and an open computational environment designed to support modeling, derivation of predictions, and exchange of data and analytical software.

Benefits of the DOE Systems Biology Knowledgebase

When fully deployed, the Knowledgebase will assume a new role for biological data management systems— from one traditionally perceived as bioinformatics support of mainstream experimental research to one in which computational analysis, modeling, and simulation capabilities drive a new era of in silico experimentation and hypothesis testing. As a unified framework linking otherwise disparate systems, the Knowledgebase will be an important tool to accelerate biological discovery for DOE missions and provide insights and benefits that can ultimately serve numerous application areas.

Democratizing Access to Experimental Data and Computational Capabilities. Biological research efforts (large and small) would gain access to dramatically more data and robust analytical and modeling tools that may not be available to smaller, individual projects. Scientists could integrate knowledge from their own research and also draw upon data generated from the entire research community.

Leveraging New Biological Insights to Advance Multiple Applications. The power of the systems approach to biology is rooted in the fact that—at the molecular level—all life is based on similar sets of fundamental processes and principles. Knowledge gained about one biological system, therefore, can advance the understanding of other systems when information is readily available in an integrated and transparent format. For example, the discovery of new regulatory pathways that influence plant biomass accumulation in bioenergy crops could also shed light on how these pathways affect carbon cycling in terrestrial vegetation or impact the productivity of agricultural crops.

Establishing the Foundation for Predictive Modeling of Biological Systems. For the first time, genomic sequence will be directly linked to the many downstream, multimodal analytical measurements of biochemical, cellular, and organismal activities. Only by developing an open infrastructure for mining, comparing, and interconnecting large biological and environmental datasets will we begin to build the comprehensive understanding needed to predict how the complex interplay between genomes and environments controls the behavior of biological systems.

Community-Driven Design of the Knowledgebase

The success of the Knowledgebase will rely largely on its ability to meet the dynamic information needs of different user communities and the willingness of these communities to support open sharing of data, science, and software.  Input and feedback from the scientific community are needed to ensure that as the Knowledgebase develops, this infrastructure provides tools and services that are valuable and useful to researchers.

To specify requirements for the Knowledgebase, the Genomic Science program is sponsoring a series of community-building workshops to engage experts from microbial genomics, plant genomics, supercomputing, and other disciplines. Output from these workshops and opportunities to contribute will be available from the DOE Systems Biology Knowledgebase Wiki site. To join the effort to draft the specifications for the Knowledgebase, go to the Wiki and select the “How to Participate” page.

Foundational Workshop for the Knowledgebase

The high-level vision for the Systems Biology Knowledgebase was defined at a May 2008 workshop hosted by DOE’s Office of Biological and Environmental Research (BER). Experts from scientific disciplines relevant to DOE missions and from the enabling technologies (e.g., bioinformatics, computer science, database development, and systems architecture) met to define the high-level vision for developing and managing a knowledgebase for OBER’s Genomic Science program (formerly Genomics:GTL). This vision was summarized in the DOE report Systems Biology Knowledgebase for a New Era in Biology.

Suggested citation for this report: U.S. DOE. 2009. U.S. Department of Energy Office of Science Systems Biology Knowledgebase for a New Era in Biology: A Genomics:GTL Report from the May 2008 Workshop, DOE/SC-113, U.S. Department of Energy Office of Science (http://genomicscience.energy.gov/compbio/).

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• Cover and Table of Contents (PDF, 208 kb)
• Executive Summary (PDF, 276 kb)
• Introduction (PDF, 1256 kb)
  
• Data, Metadata, and Information (PDF, 393 kb)
  
• Data Integration (PDF, 472 kb)
  
• Database Architecture and Infrastructure (PDF, 367 kb)
  
• GTL Knowledgebase Community and User Issues (PDF, 143 kb)
• Appendices
  
  1. Information and Data Sharing Policy (PDF, 112 kb)
     
  2. Use Case Scenarios of Systems Biology Investigations Utilizing the GTL Knowledgebase (PDF, 811 kb)
     
  3. Systems Biology for Bioenergy Solutions (PDF, 217 kb)
     
  4. Opportunities and Requirements for Research in Carbon Cycling and Environmental Remediation (PDF, 127 kb)
     
  5. Summary List of Findings from Introduction (PDF, 89 kb)
     
  6. Bibliography (PDF, 100 kb)
     
  7. Descriptions of a Selected Sampling of Databases Having Relevance to the GTL Knowledgebase (PDF, 146 kb)
     
  8. Genomics:GTL Systems Biology Knowledgebase Workshop: Agenda, Participant List, and Biosketches (PDF, 177 kb)
     
  9. Glossary (PDF, 127 kb)
     
  10. List of Web Addresses (PDF, 88 kb)
      
  11. Acronyms and Abbreviations (PDF, 137 kb)

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