Skip to main content

News about Scitation

In December 2016 Scitation will launch with a new design, enhanced navigation and a much improved user experience.

To ensure a smooth transition, from today, we are temporarily stopping new account registration and single article purchases. If you already have an account you can continue to use the site as normal.

For help or more information please visit our FAQs.

banner image
No data available.
Please log in to see this content.
You have no subscription access to this content.
No metrics data to plot.
The attempt to load metrics for this article has failed.
The attempt to plot a graph for these metrics has failed.
The full text of this article is not currently available.
/content/aip/journal/jcp/144/17/10.1063/1.4947478
1.
1.U. S. Bhalla, Prog. Biophys. Mol. Biol. 81, 45 (2003).
http://dx.doi.org/10.1016/S0079-6107(02)00046-9
2.
2.J. Ackermann, J. Einloft, J. Nöthen, and I. Koch, J. Theor. Biol. 315, 7180 (2012).
http://dx.doi.org/10.1016/j.jtbi.2012.08.042
3.
3.C. Conradi, D. Flockerzi, J. Raisch, and J. Stelling, Proc. Natl. Acad. Sci. U. S. A. 104, 19175 (2007).
http://dx.doi.org/10.1073/pnas.0705731104
4.
4.M. S. Okino and M. L. Mavrovouniotis, Chem. Rev. 98, 391 (1998).
http://dx.doi.org/10.1021/cr950223l
5.
5.O. Radulescu, A. N. Gorban, A. Zinovyev, and V. Noel, Front. Genet. 3, 131 (2012).
http://dx.doi.org/10.3389/fgene.2012.00131
6.
6.K. J. Rubin, K. Lawler, P. Sollich, and T. Ng, J. Theor. Biol. 357, 245 (2014).
http://dx.doi.org/10.1016/j.jtbi.2014.06.002
7.
7.V. Henri, C. R. Acad. Sci. Paris 135, 916 (1902).
8.
8.L. Michaelis and M. L. Menten, Biochem. Z. 49, 333 (1913).
9.
9.G. E. Briggs and J. B. S. Haldane, Biochem. J. 19, 338 (1925).
http://dx.doi.org/10.1042/bj0190338
10.
10.J. B. S. Haldane, Enzymes (Longmans, Green and Co., London, 1930).
11.
11.H. M. Sauro, Enzyme Kinetics for Systems Biology (Ambrosius Publishing, 2013).
12.
12.L. Segel and M. Slemrod, SIAM Rev. 31, 446 (1989).
http://dx.doi.org/10.1137/1031091
13.
13.D. D. Van Slyke and G. E. Cullen, J. Biol. Chem. 19, 141 (1914).
14.
14.B. Li and B. Li, J. Math. Chem. 51, 2668 (2013).
http://dx.doi.org/10.1007/s10910-013-0229-5
15.
15.R. Kollar and K. Siskova, Bull. Math. Biol. 77, 1401 (2015).
http://dx.doi.org/10.1007/s11538-015-0090-8
16.
16.H. Mori, Prog. Theor. Phys. 33, 423 (1965).
http://dx.doi.org/10.1143/PTP.33.423
17.
17.B. N. Kholodenko, O. V. Demin, G. Moehren, and J. B. Hoek, J. Biol. Chem. 274, 30169 (1999).
http://dx.doi.org/10.1074/jbc.274.42.30169
18.
18.C. M. Bishop, Pattern Recognition and Machine Learning (Springer, 2006).
19.
19.J. Murray, Mathematical Biology. I. An Introduction (Springer, New York, 2001).
20.
20.P. Thomas, A. V. Straube, and R. Grima, J. Chem. Phys. 133, 195101 (2010).
http://dx.doi.org/10.1063/1.3505552
http://aip.metastore.ingenta.com/content/aip/journal/jcp/144/17/10.1063/1.4947478
Loading
/content/aip/journal/jcp/144/17/10.1063/1.4947478
Loading

Data & Media loading...

Loading

Article metrics loading...

/content/aip/journal/jcp/144/17/10.1063/1.4947478
2016-05-06
2016-12-11

Abstract

To understand the behaviour of complex systems, it is often necessary to use models that describe the dynamics of subnetworks. It has previously been established using projection methods that such subnetwork dynamics generically involves memory of the past and that the memory functions can be calculated explicitly for biochemical reaction networks made up of unary and binary reactions. However, many established network models involve also Michaelis-Menten kinetics, to describe, e.g., enzymatic reactions. We show that the projection approach to subnetwork dynamics can be extended to such networks, thus significantly broadening its range of applicability. To derive the extension, we construct a larger network that represents enzymes and enzyme complexes explicitly, obtain the projected equations, and finally take the limit of fast enzyme reactions that gives back Michaelis-Menten kinetics. The crucial point is that this limit can be taken in closed form. The outcome is a simple procedure that allows one to obtain a description of subnetwork dynamics, including memory functions, starting directly from any given network of unary, binary, and Michaelis-Menten reactions. Numerical tests show that this closed form enzyme elimination gives a much more accurate description of the subnetwork dynamics than the simpler method that represents enzymes explicitly and is also more efficient computationally.

Loading

Full text loading...

/deliver/fulltext/aip/journal/jcp/144/17/1.4947478.html;jsessionid=216Hg6-MmNqqhubFM8s3FAPc.x-aip-live-02?itemId=/content/aip/journal/jcp/144/17/10.1063/1.4947478&mimeType=html&fmt=ahah&containerItemId=content/aip/journal/jcp
true
true

Access Key

  • FFree Content
  • OAOpen Access Content
  • SSubscribed Content
  • TFree Trial Content
752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
/content/realmedia?fmt=ahah&adPositionList=
&advertTargetUrl=//oascentral.aip.org/RealMedia/ads/&sitePageValue=jcp.aip.org/144/17/10.1063/1.4947478&pageURL=http://scitation.aip.org/content/aip/journal/jcp/144/17/10.1063/1.4947478'
Right1,Right2,Right3,