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Hartemink, A. J., Gifford, D. K., Jaakkola, T. S. and Young, R. A. (2001). Using graphical models
and genomic expression data to statistically validate models of genetic regulatory networks,
Pac. Symp. Biocomput. , pp. 441-422.
Hartig, A., Simon, M. M., Schuster, T., Daugherty, J. R., Yoo H. S. and Cooper T. G. (1992).
Differentially regulated malate synthase genes participate in carbon and nitrogen metabolism
of S.cerevisiae , Nucleic Acids Res. , 20, pp. 5677-5686.
Hartman, J. L., Garvick, B., Hartwell, L. (2001). Principles for the buffering of genetic variation,
Science , 291, pp. 1001-1004.
Heinrich, R. and Rapoport, T. A. (1974). A linear steady-state treatment of enzymatic chains.
General properties, control and effector strength, Eur. J. Biochem. , 42, pp. 89-95.
Helmstaedt, K., Strittmatter, A., Lipscomb, W. N. and Braus, G. H. (2005). Evolution of 3-deoxy-
D-arabino-heptulosonate-7-phosphate synthase-encoding genes in the yeast Saccharomyces
cerevisiae , Proc. Nat. Acad. Sci. USA , 102, pp. 9784-9789.
Hirsh, M. W. (1984). The dynamical systems approach to differential equations, Bullet. Am.
Mathemat. Soc. , 11, pp. 1-64.
Holtzhutter, H.-G. (2004). Analysis of complex metabolic networks on the basis of optimization
principles, Proc. Conference Complexity in the living , pp. 122-38.
Husmeier, D. (2003). Sensivity and specificity of inferring genetic regulatory interactions from
microarray experiments with dynamic Bayesian networks, Bionformatics , 19, pp. 2271-2282.
Ibarra, R. U., Edwards, J. S. and Palsson, B. O. (2002). Escherichia coli K-12 undergoes adaptive
evolution to achieve in silico predicted optimal growth, Nature , 420, pp. 186-189.
Ideker, T. et al. (2001). Integrating genomic and proteomic analyses of a systematically perturbed
metabolic network. Science , 292, pp. 929-934.
Jeffery, C.J. (2003). Moonlighting proteins: old proteins learning new tricks, Trends in Genetics ,
19, pp. 415-417.
Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N. and Barabasi, A. L. (2000). The large scale
organization of metabolic networks, Nature , 407, pp. 651-654.
Jones, G. E. (1978). L-asparagine auxotrophs of Saccharomyces cerevisiae : genetic and phenotypic
characterization, J. Bacteriol. , 134, pp. 200-207.
Juhnke, H., Krems, B., Kotter, P. and Entian, K.-D. (1996). Mutants that show increased sensitivity
to hydrogen peroxide reveal an important role for the pentose phosphate pathway in protection
of yeast against oxidative stress, Mol. Gen. Genet. , 252, pp. 456-464.
Kacser, H. and Burns, J. A. (1973). The control of flux, Symp. Soc. Exp. Biol. , 27, pp. 65-104.
Kastanos, E. K., Woldman, Y. Y. and Appling, D. R. (1997). Role of mitochondrial and
cytoplasmic serine hydroxymethyltransferase isozymes in de novo purine synthesis in
Saccharomyces cerevisiae , Biochemistry , 36, pp. 14956-14964.
Klamt, S. and Stelling, J.(2003). Stoichiometric analysis of metabolic networks, Tutorial at the 4th
International Conference on Systems Biology.
Krishnan, A., Giuliani, A., Zbilut, J. P. and Tomita, M. (2007). Network scaling invariants help to
elucidate basic topological principles of proteins, Journal of proteome research , 6, pp. 3924-
3934.
Kuepfer, L., Sauer, U. and Blank, L. M. (2005). Metabolic functions of duplicated genes in
Saccharomyces cerevisiae , Genome Res. , 15, pp. 1421-1430.
Kusano, M., Sakai, Y., Kato, N., Yoshimoto, H., Sone, H. and Tamai, Y. (1998). Hemiacetal
dehydrogenation activity of Alcohol dehydrogenases in Saccharomyces cerevisiae , Biosci.
Biotechnol. Biochem. , 62, pp. 1956-1961.
Lässig, M., Bastolla, U., Manrubia, S. C. and Valleriani, A. (2001). Shape of Ecological Networks,
Phys. Rev. Lett. , 86, pp. 4418-4421.
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