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Items: 1 to 20 of 95

1.

In silico method for modelling metabolism and gene product expression at genome scale.

Lerman JA, Hyduke DR, Latif H, Portnoy VA, Lewis NE, Orth JD, Schrimpe-Rutledge AC, Smith RD, Adkins JN, Zengler K, Palsson BO.

Nat Commun. 2012 Jul 3;3:929. doi: 10.1038/ncomms1928.

2.

Systems biology of the structural proteome.

Brunk E, Mih N, Monk J, Zhang Z, O'Brien EJ, Bliven SE, Chen K, Chang RL, Bourne PE, Palsson BO.

BMC Syst Biol. 2016 Mar 11;10:26. doi: 10.1186/s12918-016-0271-6.

3.

Analysis of the Thermotoga maritima genome combining a variety of sequence similarity and genome context tools.

Kyrpides NC, Ouzounis CA, Iliopoulos I, Vonstein V, Overbeek R.

Nucleic Acids Res. 2000 Nov 15;28(22):4573-6.

4.

Diversity and versatility of the Thermotoga maritima sugar kinome.

Rodionova IA, Yang C, Li X, Kurnasov OV, Best AA, Osterman AL, Rodionov DA.

J Bacteriol. 2012 Oct;194(20):5552-63. Epub 2012 Aug 10.

5.

Systems biology as a foundation for genome-scale synthetic biology.

Barrett CL, Kim TY, Kim HU, Palsson BØ, Lee SY.

Curr Opin Biotechnol. 2006 Oct;17(5):488-92. Epub 2006 Aug 23. Review.

PMID:
16934450
6.

Multi -omics and metabolic modelling pipelines: challenges and tools for systems microbiology.

Fondi M, Liò P.

Microbiol Res. 2015 Feb;171:52-64. doi: 10.1016/j.micres.2015.01.003. Epub 2015 Jan 7. Review.

7.

Comprehensive evaluation of two genome-scale metabolic network models for Scheffersomyces stipitis.

Damiani AL, He QP, Jeffries TW, Wang J.

Biotechnol Bioeng. 2015 Jun;112(6):1250-62. doi: 10.1002/bit.25535. Epub 2015 Mar 21.

PMID:
25580821
8.

Using Genome-scale Models to Predict Biological Capabilities.

O'Brien EJ, Monk JM, Palsson BO.

Cell. 2015 May 21;161(5):971-987. doi: 10.1016/j.cell.2015.05.019. Review.

9.

Triad pattern algorithm for predicting strong promoter candidates in bacterial genomes.

Dekhtyar M, Morin A, Sakanyan V.

BMC Bioinformatics. 2008 May 9;9:233. doi: 10.1186/1471-2105-9-233.

10.

Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox.

Becker SA, Feist AM, Mo ML, Hannum G, Palsson BØ, Herrgard MJ.

Nat Protoc. 2007;2(3):727-38.

PMID:
17406635
11.

A genome-scale, constraint-based approach to systems biology of human metabolism.

Mo ML, Jamshidi N, Palsson BØ.

Mol Biosyst. 2007 Sep;3(9):598-603. Epub 2007 Jul 11.

PMID:
17700859
12.

The genome organization of Thermotoga maritima reflects its lifestyle.

Latif H, Lerman JA, Portnoy VA, Tarasova Y, Nagarajan H, Schrimpe-Rutledge AC, Smith RD, Adkins JN, Lee DH, Qiu Y, Zengler K.

PLoS Genet. 2013 Apr;9(4):e1003485. doi: 10.1371/journal.pgen.1003485. Epub 2013 Apr 25.

13.

Three-dimensional structural view of the central metabolic network of Thermotoga maritima.

Zhang Y, Thiele I, Weekes D, Li Z, Jaroszewski L, Ginalski K, Deacon AM, Wooley J, Lesley SA, Wilson IA, Palsson B, Osterman A, Godzik A.

Science. 2009 Sep 18;325(5947):1544-9. doi: 10.1126/science.1174671.

14.

Probabilistic integrative modeling of genome-scale metabolic and regulatory networks in Escherichia coli and Mycobacterium tuberculosis.

Chandrasekaran S, Price ND.

Proc Natl Acad Sci U S A. 2010 Oct 12;107(41):17845-50. doi: 10.1073/pnas.1005139107. Epub 2010 Sep 27.

15.

The emerging CHO systems biology era: harnessing the 'omics revolution for biotechnology.

Kildegaard HF, Baycin-Hizal D, Lewis NE, Betenbaugh MJ.

Curr Opin Biotechnol. 2013 Dec;24(6):1102-7. doi: 10.1016/j.copbio.2013.02.007. Epub 2013 Mar 20. Review.

PMID:
23523260
16.

iTAP: integrated transcriptomics and phenotype database for stress response of Escherichia coli and Saccharomyces cerevisiae.

Sundararaman N, Ash C, Guo W, Button R, Singh J, Feng X.

BMC Res Notes. 2015 Dec 12;8:771. doi: 10.1186/s13104-015-1759-7.

17.

Metabolic fluxes and beyond-systems biology understanding and engineering of microbial metabolism.

Kohlstedt M, Becker J, Wittmann C.

Appl Microbiol Biotechnol. 2010 Nov;88(5):1065-75. doi: 10.1007/s00253-010-2854-2. Epub 2010 Sep 7. Review.

PMID:
20821203
18.

Green systems biology - From single genomes, proteomes and metabolomes to ecosystems research and biotechnology.

Weckwerth W.

J Proteomics. 2011 Dec 10;75(1):284-305. doi: 10.1016/j.jprot.2011.07.010. Epub 2011 Jul 23. Review.

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.

From -omics to personalized medicine in nephrology: integration is the key.

Pesce F, Pathan S, Schena FP.

Nephrol Dial Transplant. 2013 Jan;28(1):24-8. doi: 10.1093/ndt/gfs483. Epub 2012 Dec 9. Review.

PMID:
23229923

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