Format
Sort by
Items per page

Send to

Choose Destination

Links from PubMed

Items: 1 to 20 of 155

1.

Impact of stoichiometry representation on simulation of genotype-phenotype relationships in metabolic networks.

Brochado AR, Andrejev S, Maranas CD, Patil KR.

PLoS Comput Biol. 2012;8(11):e1002758. doi: 10.1371/journal.pcbi.1002758. Epub 2012 Nov 1.

3.

Path finding methods accounting for stoichiometry in metabolic networks.

Pey J, Prada J, Beasley JE, Planes FJ.

Genome Biol. 2011;12(5):R49. doi: 10.1186/gb-2011-12-5-r49. Epub 2011 May 27.

4.

Evolutionary programming as a platform for in silico metabolic engineering.

Patil KR, Rocha I, Förster J, Nielsen J.

BMC Bioinformatics. 2005 Dec 23;6:308.

5.

Dynamic estimation of specific fluxes in metabolic networks using non-linear dynamic optimization.

Vercammen D, Logist F, Impe JV.

BMC Syst Biol. 2014 Dec 3;8:132. doi: 10.1186/s12918-014-0132-0.

6.

Towards kinetic modeling of genome-scale metabolic networks without sacrificing stoichiometric, thermodynamic and physiological constraints.

Chakrabarti A, Miskovic L, Soh KC, Hatzimanikatis V.

Biotechnol J. 2013 Sep;8(9):1043-57. doi: 10.1002/biot.201300091. Epub 2013 Aug 20.

PMID:
23868566
7.

OptFlux: an open-source software platform for in silico metabolic engineering.

Rocha I, Maia P, Evangelista P, Vilaça P, Soares S, Pinto JP, Nielsen J, Patil KR, Ferreira EC, Rocha M.

BMC Syst Biol. 2010 Apr 19;4:45. doi: 10.1186/1752-0509-4-45.

8.

Inferring branching pathways in genome-scale metabolic networks.

Pitkänen E, Jouhten P, Rousu J.

BMC Syst Biol. 2009 Oct 29;3:103. doi: 10.1186/1752-0509-3-103.

9.

Natural computation meta-heuristics for the in silico optimization of microbial strains.

Rocha M, Maia P, Mendes R, Pinto JP, Ferreira EC, Nielsen J, Patil KR, Rocha I.

BMC Bioinformatics. 2008 Nov 27;9:499. doi: 10.1186/1471-2105-9-499.

10.

Predicting biological system objectives de novo from internal state measurements.

Gianchandani EP, Oberhardt MA, Burgard AP, Maranas CD, Papin JA.

BMC Bioinformatics. 2008 Jan 24;9:43. doi: 10.1186/1471-2105-9-43.

11.

FCDECOMP: decomposition of metabolic networks based on flux coupling relations.

Rezvan A, Marashi SA, Eslahchi C.

J Bioinform Comput Biol. 2014 Oct;12(5):1450028. doi: 10.1142/S0219720014500280.

PMID:
25362842
12.
13.

Symbolic flux analysis for genome-scale metabolic networks.

Schryer DW, Vendelin M, Peterson P.

BMC Syst Biol. 2011 May 23;5:81. doi: 10.1186/1752-0509-5-81.

14.

Exploiting stoichiometric redundancies for computational efficiency and network reduction.

Ingalls BP, Bembenek E.

In Silico Biol. 2015;12(1-2):55-67. doi: 10.3233/ISB-140464. Review.

15.

Estimating the size of the solution space of metabolic networks.

Braunstein A, Mulet R, Pagnani A.

BMC Bioinformatics. 2008 May 19;9:240. doi: 10.1186/1471-2105-9-240.

16.

A hybrid model of anaerobic E. coli GJT001: combination of elementary flux modes and cybernetic variables.

Kim JI, Varner JD, Ramkrishna D.

Biotechnol Prog. 2008 Sep-Oct;24(5):993-1006. doi: 10.1002/btpr.73.

PMID:
19194908
17.

regEfmtool: speeding up elementary flux mode calculation using transcriptional regulatory rules in the form of three-state logic.

Jungreuthmayer C, Ruckerbauer DE, Zanghellini J.

Biosystems. 2013 Jul;113(1):37-9. doi: 10.1016/j.biosystems.2013.04.002. Epub 2013 May 7.

PMID:
23664840
18.

Using bioconductor package BiGGR for metabolic flux estimation based on gene expression changes in brain.

Gavai AK, Supandi F, Hettling H, Murrell P, Leunissen JA, van Beek JH.

PLoS One. 2015 Mar 25;10(3):e0119016. doi: 10.1371/journal.pone.0119016. eCollection 2015.

19.

Prediction of metabolic flux distribution from gene expression data based on the flux minimization principle.

Song HS, Reifman J, Wallqvist A.

PLoS One. 2014 Nov 14;9(11):e112524. doi: 10.1371/journal.pone.0112524. eCollection 2014.

20.

Predictive potential of flux balance analysis of Saccharomyces cerevisiae using as optimization function combinations of cell compartmental objectives.

García Sánchez CE, Vargas García CA, Torres Sáez RG.

PLoS One. 2012;7(8):e43006. doi: 10.1371/journal.pone.0043006. Epub 2012 Aug 9.

Supplemental Content

Support Center