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    [1]
    [2] Zaslaver A, Mayo AE, Rosenberg R, Bashkin P, Sberro H, Tsalyuk M, Surette MG, and Alon U. Just-in-time transcription program in metabolic pathways. Nat. Gen, 36:486–491, 2004. 379

    [3] Caroline Coljin. Interpreting expression data with metabolic flux models: Predicting mycobacterium tuberculosis mycolic acid production. PLoS Computational Biology, 5(8), Aug 2009.

    [4] Price N. D., Reed J. L., Papin J.A, Famili I., and Palsson B.O. Analysis of metabolic capabilities using singular value decomposition of extreme pathway matrices. Biophys J., 84(2):794–804, Feb 2003.

    [5] Gasteiger E., Gattiker A., Hoogland C. andIvanyi I., Appel R.D., , and Bairoch A. Expasy: The proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res, 31(13):3784–3788.

    [6] J.S. Edwards, R. U. Ibarra, and B.O. Palsson. In silico predictions of e coli metabolic capabilities are consis ent with experimental data. Nat Biotechnology, 19:125–130, 2001.

    [7] Covert M et al. Regulation of gene expression in flux balance models of metabolism. Journal of Theoretical Biology, 213:73–88, Nov 2001.

    [8] J. Forster, I. Famili, B.O. Palsson, and J. Nielsen. Large-scale evaluation of in silico gene deletions in saccharomyces cerevisiae. OMICS, 7(2):193–202, 2003. PMID: 14506848.

    [9] Boshoff H.I., Myers T.G., Copp B.R., McNeil M.R., Wilson M.A., and Bary C.E. The transcriptional response of mycobacterium tuberculosis to inhibitors of metabolism: novel insights into drug mechanisms of action. J Biol Chem, 279:40174–40184, Sep 2004.

    [10] Holmberg. On the practical identifiability of microbial-growth models incorporating michaelis-menten type nonlinearities. Mathematical Biosciences, 62(1):23–43, 1982.

    [11] Edwards J.S. and Palsson B.O. volume 97, pages 5528–5533. Proceedings of the National Academy of Sciences of the United States of America, May 2000. PMC25862.

    [12] Edwards J.S., Covert M., , and Palsson B. Metabolic modeling of microbes: the flux balance approach. Environmental Microbiology, 4(3):133–140, 2002.

    [13] Raman Karthik, Preethi Rajagopalan, and Nagasuma Chandra. Flux balance analysis of mycolic acid pathway: Targets for anti-tubercular drugs. PLoS Computational Biology, 1, Oct 2005.

    [14] Kanehisa M., Goto S., Kawashima S., and Nakaya. From genomics to chemical genomics: new devel- opments in kegg. Nucleic Acids Res., 34, 2006.

    [15] Jamshidi N. and Palsson B. Investigating the metabolic capabilities of mycobacterium tuberculosis h37rv using the in silico strain inj661 and proposing alternative drug targets. BMC Systems Biology, 26, 2007.

    [16] Caspi R., Foerster H., Fulcher C.A., Kaipa P., Krummenacker M., Latendresse M., Paley S., Rhee S.Y., Shearer A.G., Tissier C., Walk T.C. ZhangP., and Karp P. The metacyc database of metabolic pathways and enzymes and the biocyc collection of pathway/genome databases. Nucleic Acids Res, 36(Suppl), 2008.

    [17] A. Varma and B. O. Palsson. Stoichiometric flux balance models quantitatively predict growth and metabolic by-product secretion in wild-type escherichia coli w3110. Applied and Environmental Micro- biology, 60:3724–3731, Oct 1994.


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