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Title: Final report for U.S. Department of Energy Award DE-SC0010429 to the University of Luxembourg on Multi-scale Molecular Systems Biology: Reconstruction and Model Optimization

Abstract

Within the Biological and Environmental Research program, the goal of the Genomic Science program is to achieve a predictive, systems-level understanding of plants, microbes, and biological communities to enable biobased solutions to DOE mission challenges in energy and environment. To achieve this goal, an ultimate objective is to develop the knowledgebase, computational infrastructure, and modeling capabilities to advance predictive understanding and manipulation of biological systems. Our project has increased the modeling capabilities and computational infrastructure required to advance predictive understanding and manipulation of biological systems. In particular, we have developed novel algorithms, for modelling biochemical reaction kinetics at genome-scale. These new algorithms have been publicly disseminated as open source software with extensive documentation and tutorials that enable widespread application of this advanced software to practical modelling scenarios. The technical effectiveness of all novel software has been conclusively demonstrated and the quality of this software is maintained by a dedicated continuous integration system. Ultimately, the results of this project will benefit the public because it will enable biologists to more accurately computationally model biological systems that need to be understood to address DOE challenges in energy and environment.

Authors:
ORCiD logo [1]
  1. Leiden Univ. (Netherlands)
Publication Date:
Research Org.:
University of Luxembourg
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
OSTI Identifier:
1572377
Report Number(s):
DE-SC0010429-FINAL
DOE Contract Number:  
SC0010429
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; 97 MATHEMATICS AND COMPUTING; 09 BIOMASS FUELS; Biochemical networks, kinetic modelling, fluxomics

Citation Formats

Fleming, Ronan. Final report for U.S. Department of Energy Award DE-SC0010429 to the University of Luxembourg on Multi-scale Molecular Systems Biology: Reconstruction and Model Optimization. United States: N. p., 2019. Web. doi:10.2172/1572377.
Fleming, Ronan. Final report for U.S. Department of Energy Award DE-SC0010429 to the University of Luxembourg on Multi-scale Molecular Systems Biology: Reconstruction and Model Optimization. United States. doi:10.2172/1572377.
Fleming, Ronan. Wed . "Final report for U.S. Department of Energy Award DE-SC0010429 to the University of Luxembourg on Multi-scale Molecular Systems Biology: Reconstruction and Model Optimization". United States. doi:10.2172/1572377. https://www.osti.gov/servlets/purl/1572377.
@article{osti_1572377,
title = {Final report for U.S. Department of Energy Award DE-SC0010429 to the University of Luxembourg on Multi-scale Molecular Systems Biology: Reconstruction and Model Optimization},
author = {Fleming, Ronan},
abstractNote = {Within the Biological and Environmental Research program, the goal of the Genomic Science program is to achieve a predictive, systems-level understanding of plants, microbes, and biological communities to enable biobased solutions to DOE mission challenges in energy and environment. To achieve this goal, an ultimate objective is to develop the knowledgebase, computational infrastructure, and modeling capabilities to advance predictive understanding and manipulation of biological systems. Our project has increased the modeling capabilities and computational infrastructure required to advance predictive understanding and manipulation of biological systems. In particular, we have developed novel algorithms, for modelling biochemical reaction kinetics at genome-scale. These new algorithms have been publicly disseminated as open source software with extensive documentation and tutorials that enable widespread application of this advanced software to practical modelling scenarios. The technical effectiveness of all novel software has been conclusively demonstrated and the quality of this software is maintained by a dedicated continuous integration system. Ultimately, the results of this project will benefit the public because it will enable biologists to more accurately computationally model biological systems that need to be understood to address DOE challenges in energy and environment.},
doi = {10.2172/1572377},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {10}
}

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