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Items: 1 to 20 of 129

1.

Decoding complex biological networks - tracing essential and modulatory parameters in complex and simplified models of the cell cycle.

Eriksson O, Andersson T, Zhou Y, Tegnér J.

BMC Syst Biol. 2011 Aug 7;5:123. doi: 10.1186/1752-0509-5-123.

2.

Communicating oscillatory networks: frequency domain analysis.

Ihekwaba AE, Sedwards S.

BMC Syst Biol. 2011 Dec 22;5:203. doi: 10.1186/1752-0509-5-203.

3.

PeTTSy: a computational tool for perturbation analysis of complex systems biology models.

Domijan M, Brown PE, Shulgin BV, Rand DA.

BMC Bioinformatics. 2016 Mar 10;17:124. doi: 10.1186/s12859-016-0972-2.

4.

Dynamical and topological robustness of the mammalian cell cycle network: a reverse engineering approach.

Ruz GA, Goles E, Montalva M, Fogel GB.

Biosystems. 2014 Jan;115:23-32. doi: 10.1016/j.biosystems.2013.10.007. Epub 2013 Nov 6.

PMID:
24212100
5.

Parametric sensitivity analysis for biochemical reaction networks based on pathwise information theory.

Pantazis Y, Katsoulakis MA, Vlachos DG.

BMC Bioinformatics. 2013 Oct 22;14:311. doi: 10.1186/1471-2105-14-311.

6.

A data integration approach for cell cycle analysis oriented to model simulation in systems biology.

Alfieri R, Merelli I, Mosca E, Milanesi L.

BMC Syst Biol. 2007 Aug 1;1:35.

7.

A hybrid model of cell cycle in mammals.

Behaegel J, Comet JP, Bernot G, Cornillon E, Delaunay F.

J Bioinform Comput Biol. 2016 Feb;14(1):1640001. doi: 10.1142/S0219720016400011. Epub 2015 Nov 23.

PMID:
26708052
8.

Novel recurrent neural network for modelling biological networks: oscillatory p53 interaction dynamics.

Ling H, Samarasinghe S, Kulasiri D.

Biosystems. 2013 Dec;114(3):191-205. doi: 10.1016/j.biosystems.2013.08.004. Epub 2013 Sep 5.

PMID:
24012741
9.

Understanding dynamics using sensitivity analysis: caveat and solution.

Perumal TM, Gunawan R.

BMC Syst Biol. 2011 Mar 15;5:41. doi: 10.1186/1752-0509-5-41.

10.

Model-Based Analysis of Cell Cycle Responses to Dynamically Changing Environments.

Seaton DD, Krishnan J.

PLoS Comput Biol. 2016 Jan 7;12(1):e1004604. doi: 10.1371/journal.pcbi.1004604. eCollection 2016 Jan.

11.
12.

Representing perturbed dynamics in biological network models.

Stoll G, Rougemont J, Naef F.

Phys Rev E Stat Nonlin Soft Matter Phys. 2007 Jul;76(1 Pt 1):011917. Epub 2007 Jul 25.

PMID:
17677504
13.

Modular logical modelling of the budding yeast cell cycle.

Fauré A, Naldi A, Lopez F, Chaouiya C, Ciliberto A, Thieffry D.

Mol Biosyst. 2009 Dec;5(12):1787-96. doi: 10.1039/B910101m. Epub 2009 Jul 31.

PMID:
19763337
14.

Dynamics of the cell-cycle network under genome-rewiring perturbations.

Katzir Y, Elhanati Y, Averbukh I, Braun E.

Phys Biol. 2013 Dec;10(6):066001. doi: 10.1088/1478-3975/10/6/066001. Epub 2013 Oct 28.

PMID:
24162518
15.

Estimating confidence intervals in predicted responses for oscillatory biological models.

St John PC, Doyle FJ 3rd.

BMC Syst Biol. 2013 Jul 29;7:71. doi: 10.1186/1752-0509-7-71.

16.

Modeling the cell cycle: from deterministic models to hybrid systems.

Alfieri R, Bartocci E, Merelli E, Milanesi L.

Biosystems. 2011 Jul;105(1):34-40. doi: 10.1016/j.biosystems.2011.03.002. Epub 2011 Mar 29.

PMID:
21453748
17.

Efficient characterization of high-dimensional parameter spaces for systems biology.

Zamora-Sillero E, Hafner M, Ibig A, Stelling J, Wagner A.

BMC Syst Biol. 2011 Sep 15;5:142. doi: 10.1186/1752-0509-5-142.

18.

Design of biomolecular network modifications to achieve adaptation.

Waldherr S, Streif S, Allgöwer F.

IET Syst Biol. 2012 Dec;6(6):223-31.

PMID:
23560327
19.

Computational systems biology and dose-response modeling in relation to new directions in toxicity testing.

Zhang Q, Bhattacharya S, Andersen ME, Conolly RB.

J Toxicol Environ Health B Crit Rev. 2010 Feb;13(2-4):253-76. doi: 10.1080/10937404.2010.483943.

PMID:
20574901
20.

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