TY - JOUR
T1 - All systems go
T2 - Launching cell simulation fueled by integrated experimental biology data
AU - Arita, Masanori
AU - Robert, Martin
AU - Tomita, Masaru
N1 - Funding Information:
The authors wish to thank Takaaki Nishioka, Tomoyoshi Soga, Tomoya Baba and Nobuyoshi Ishii (Keio University) for discussion and suggestions on the manuscript. This work was supported by (i) MEXT, Grant-in-Aid for Scientific Research on Priority Areas ‘Genome information science’, Grant-in-aid for the 21st century Center of Excellence (COE) program ‘Understanding and control of life's function via systems biology’, and Leading project for biosimulation; (ii) METI, NEDO project ‘Development of a Technological Infrastructure for Industrial Bioprocess Project’; and (iii) the Japan Science and Technology Agency (JST). MA is a Precursory Research for Embryonic Science and Technology, Japan Science and Technology Agency, (PRESTO-JST) funded investigator.
PY - 2005/6
Y1 - 2005/6
N2 - Biological simulation serves to unify the basic elements of systems biology, namely, model selection, experimentation and model refinement. To select biochemical models for simulation, metabolome analysis can be performed using capillary electrophoresis or liquid chromatography coupled with mass spectrometry. In this manner, selected models can be elaborated with temporal/spatial gene and protein expression data obtained from model organisms such as Escherichia coli. The E. coli single gene deletion mutant library (KO collection) and His-tag/GFP-fusion single open reading frame clone expression library (ASKA) are powerful resources for this task. The integration of parallel experimental datasets into dynamic simulation tools forms the remaining challenge for the systematic analysis and elucidation of biological networks and holds promise for biotechnological applications.
AB - Biological simulation serves to unify the basic elements of systems biology, namely, model selection, experimentation and model refinement. To select biochemical models for simulation, metabolome analysis can be performed using capillary electrophoresis or liquid chromatography coupled with mass spectrometry. In this manner, selected models can be elaborated with temporal/spatial gene and protein expression data obtained from model organisms such as Escherichia coli. The E. coli single gene deletion mutant library (KO collection) and His-tag/GFP-fusion single open reading frame clone expression library (ASKA) are powerful resources for this task. The integration of parallel experimental datasets into dynamic simulation tools forms the remaining challenge for the systematic analysis and elucidation of biological networks and holds promise for biotechnological applications.
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U2 - 10.1016/j.copbio.2005.04.004
DO - 10.1016/j.copbio.2005.04.004
M3 - Review article
C2 - 15961035
AN - SCOPUS:20444396593
SN - 0958-1669
VL - 16
SP - 344
EP - 349
JO - Current Opinion in Biotechnology
JF - Current Opinion in Biotechnology
IS - 3 SPEC. ISS.
ER -