Systems biology-An engineering perspective

A. Kremling; J. Saez-Rodriguez

doi:10.1016/j.jbiotec.2007.02.009

Systems biology-An engineering perspective

A. Kremling
, J. Saez-Rodriguez

Max Planck Institute for Dynamics of Complex Technical Systems

Research output: Contribution to journal › Article › peer-review

59 Scopus citations

Abstract

The interdisciplinary field of systems biology has evolved rapidly over the last years. Different disciplines have aided the development of both its experimental and theoretical branches. One field, which has played a significant role is engineering science and, in particular chemical engineering. Here, we review and illustrate some of these contributions, ranging from modeling approaches to model analysis with a special focus on technique which have not yet been substantially exploited but can be potentially useful in the analysis of biochemical systems.

Original language	English
Pages (from-to)	329-351
Number of pages	23
Journal	Journal of Biotechnology
Volume	129
Issue number	2
DOIs	https://doi.org/10.1016/j.jbiotec.2007.02.009
State	Published - 30 Apr 2007
Externally published	Yes

Keywords

Control engineering
Model reduction
Model verification
Modeling framework

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10.1016/j.jbiotec.2007.02.009

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title = "Systems biology-An engineering perspective",

abstract = "The interdisciplinary field of systems biology has evolved rapidly over the last years. Different disciplines have aided the development of both its experimental and theoretical branches. One field, which has played a significant role is engineering science and, in particular chemical engineering. Here, we review and illustrate some of these contributions, ranging from modeling approaches to model analysis with a special focus on technique which have not yet been substantially exploited but can be potentially useful in the analysis of biochemical systems.",

keywords = "Control engineering, Model reduction, Model verification, Modeling framework",

author = "A. Kremling and J. Saez-Rodriguez",

note = "Funding Information: The authors thank R. Schenkendorf for performing the calculations with the Kalman-Filter, and J. Huard, H. Conzelmann and S. Klamt for critical reading the manuscript, and D. Flockerzi for references on time-scale-based model reduction. J.S.R. acknowledges founding of the German Research Foundation (FOR521).",

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doi = "10.1016/j.jbiotec.2007.02.009",

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AU - Saez-Rodriguez, J.

N1 - Funding Information: The authors thank R. Schenkendorf for performing the calculations with the Kalman-Filter, and J. Huard, H. Conzelmann and S. Klamt for critical reading the manuscript, and D. Flockerzi for references on time-scale-based model reduction. J.S.R. acknowledges founding of the German Research Foundation (FOR521).

PY - 2007/4/30

Y1 - 2007/4/30

N2 - The interdisciplinary field of systems biology has evolved rapidly over the last years. Different disciplines have aided the development of both its experimental and theoretical branches. One field, which has played a significant role is engineering science and, in particular chemical engineering. Here, we review and illustrate some of these contributions, ranging from modeling approaches to model analysis with a special focus on technique which have not yet been substantially exploited but can be potentially useful in the analysis of biochemical systems.

AB - The interdisciplinary field of systems biology has evolved rapidly over the last years. Different disciplines have aided the development of both its experimental and theoretical branches. One field, which has played a significant role is engineering science and, in particular chemical engineering. Here, we review and illustrate some of these contributions, ranging from modeling approaches to model analysis with a special focus on technique which have not yet been substantially exploited but can be potentially useful in the analysis of biochemical systems.

KW - Control engineering

KW - Model reduction

KW - Model verification

KW - Modeling framework

UR - https://www.scopus.com/pages/publications/34047213964

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DO - 10.1016/j.jbiotec.2007.02.009

M3 - Article

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SN - 0168-1656

VL - 129

SP - 329

EP - 351

JO - Journal of Biotechnology

JF - Journal of Biotechnology

IS - 2

ER -

Systems biology-An engineering perspective

Abstract

Keywords

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