1 / 8

ASCAC-BERAC Joint Panel on Accelerating Progress Toward GTL Goals

ASCAC-BERAC Joint Panel on Accelerating Progress Toward GTL Goals. Some concerns that were expressed by ASCAC members. Summary of Concerns. Growing Divergence Between ASCR and BER goals Current BERAC definitions create a very high risk of failure

masako
Download Presentation

ASCAC-BERAC Joint Panel on Accelerating Progress Toward GTL Goals

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. ASCAC-BERAC Joint Panel on Accelerating Progress Toward GTL Goals Some concerns that were expressed by ASCAC members

  2. Summary of Concerns • Growing Divergence Between ASCR and BER goals • Current BERAC definitions create a very high risk of failure • Lack of clarity with regard to program responsibilities • Lack of prioritization for resource constrained scenarios • Lack of intermediate goals that would provide true indicators of success/concern • Need for a follow-up study

  3. Growing Divergence Between ASCR and BER goals • (2008) “The ten-year OMB PART goal for ASCR for the joint modeling and simulation activity of ASCR and BER should be modified to read as follows: • (ASCR) By 2018, demonstrate significant advances in the capability to predict an organism’s phenotype from its genome sequence, through advances in genome sequence annotation, whole genome modeling and simulation, and integrated model-driven experimentation. • (2006) “BERAC proposes the following as a replacement for the Life Sciences PART measure: • By 2015, provide sufficient scientific understanding of plants and microbes to develop robust new strategies to produce biofuels, clean up waste, or sequester carbon. This includes research that supports the development of computational models to direct the use and design of improved organisms carrying out these processes.

  4. Current BERAC definitions create a very high risk of failure • (2006) BERAC proposes the following “grading” scale for the revised PART measure: • Excellent: Systems biology understanding and computational models that accurately describe the capabilities and potential of key processes in microbes, microbial communities, or plants for production of biofuels, to clean up waste, or to sequester carbon are developed and validated experimentally by the use or reengineering of those microbes, microbial communities or plants based on model predictions. • Good: Systems biology understanding and computational models that accurately describe the potential of key microbes, microbial communities, or plants for production of biofuels, to clean up waste, or to sequester carbon are developed and validated by their consistency with available data. • Fair: Systems biology understanding and computational models that describe the potential of key microbes, microbial communities or plants for production of biofuels, to clean up waste, or to sequester carbon are developed but are not yet validated. • Poor: Systems biology understanding of the potential of key microbes, microbial communities or plants for production of biofuels, to clean up waste, or to sequester carbon is developed but robust computational models describing these systems are not developed. • BER automatically gets “Poor” without ASCR and suggested revision of ASCR goal generates a disconnect that may result in failure for both programs.

  5. Lack of clarity with regard to program responsibilities • Recommendation 5, is notable for identifying the roles of each program. This should be explicitly included in all of the recommendations. • Recommendation 5. DOE should establish a mechanism to support the long-term curation and integration of genomics and related datasets (annotations, metabolic reconstructions, expression data, whole genome screens, phenotype data, etc.) to support biological research in general and specifically the needs of modeling and simulation in particular in areas of energy and the environment that are not well supported by NSF and NIH. This mechanism should target the creation of a state-of-the-art community resource for data of all forms that are relevant to organisms of interest to DOE. This should be a joint activity of ASCR and BER, with ASCR responsible for the database and computational infrastructure to enable community annotation and data sharing. It should also leverage the work of established groups.

  6. Lack of prioritization for resource constrained scenarios • The report needs to provide an order of magnitude for a funding envelope for “appropriate scale” and should identifypriorities in the face of almost certain resource constraints. • ASCAC discussion regarding the ASCR portfolio indicated that the ASCR resources available for this effort (~$2M in FY08) will not grow significantly in the goal time horizon. • BER resources directly relevant to this effort are higher but the same order of magnitude (~$5M).

  7. Lack of intermediate goals that would provide true indicators of success/concern • The report identified two general areas for intermediate goals but these are, as a set, neither necessary nor sufficient to assess progress, or lack of progress, toward the goal. • “Intermediate goals that could be considered more relevant for the two programs fall into two general areas. The first area is building needed tools, curated databases, and computational and collaborative infrastructure that directly support accelerating the communities’ ability to develop models and simulations. Examples of these are tools for curation of genomes and reconstruction of metabolic networks, integrated databases enabling the community to share data needed to build and test models and validation datasets, and mathematical libraries and core model components that would enable many groups to leverage the work of others. The second area is focusing on a targeted set of biological modeling and simulations problems that build on each other and that over time would expand the modeling capabilities in the appropriate directions. Examples of these are models of cellular metabolism, motility, global transcription regulation and differentiation, and life-cycle development. Each of these models could play a role in advancing toward the overarching goal of a complete cell model that can be used to predict phenotypic traits or behaviors of a cell from genomic and other “omic” data sources.”

  8. Need for a follow-up Study • Recommendation 2 implies the need for a follow-up joint study that brings together the two communities. • “Recommendation 2. DOE should develop an explicit research program aimed at achieving significant progress on the overarching goal of predictive modeling and simulation in DOE relevant biological systems. This program should be a joint effort between ASCR and BER and should include a diversity of modeling approaches. The program should leverage existing experimental activities as well as support the development of new experimental activities that are directly tied to the needs of developing predictive models. This new research program should be aimed at advancing the state of the art of cell modeling directly, should include equal participation from biologists and mathematicians, computer scientists, and engineers; and should be indirectly coupled to the more applied goals of bioenergy, carbon cycle research, or bioremediation. This program will need to be supported at a large-enough scale that a multiple-target approach can be pursued that will enable progress on many intermediate goals simultaneously by different research groups.” • This needs to be community driven. 

More Related