Metabolic flux correlations, genetic interactions, and disease

Journal of Computational Biology

Volumn 16, Issue 2, 2009, Pages 291-302

  Veeramani, Balaji ^b   Bader, Joel S ^a  

^a Johns Hopkins University   (United States)

^b NONE

Author keywords

Flux balance analysis; Metabolic network; OMIM; Synthetic lethal genetic interactions; Systems biology

Indexed keywords

ENZYME;

ARTICLE; CELL DEATH; CONTROLLED STUDY; ENZYME BINDING; EPISTASIS; GENE INTERACTION; GENE MUTATION; GENETIC DISORDER; MATHEMATICAL MODEL; METABOLISM; METABOLITE; NONHUMAN; PHENOTYPE; PRIORITY JOURNAL; YEAST;

DISEASE; ENZYMES; EPISTASIS, GENETIC; HUMANS; METABOLIC NETWORKS AND PATHWAYS; MODELS, BIOLOGICAL; MUTATION; PHENOTYPE; SACCHAROMYCES CEREVISIAE;

EID: 59649083192     PISSN: 10665277     EISSN: None     Source Type: Journal    
DOI: 10.1089/cmb.2008.14TT     Document Type: Article

References (30)

1. Almaas, E., Kovacs, B., Vicsek, T., et al. 2004. Global organization of metabolic fluxes in the bacterium Escherichia coli. Nature 427, 839-843.
2. Banker, G., and Goslin, K., eds. 1998. Culturing Nerve Cells. MIT Press, Cambridge, MA.
3. Becker, S.A., Feist, A.M., Mo, M.L., et al. 2007. Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nat. Protoc. 2, 727-738.
4. Duarte, N.C., Becker, S.A., Jamshidi, N., et al. 2007. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc. Natl. Acad. Sci. USA 104, 1777-1782.
5. Duarte, N.C., Herrgard, M.J., and Palsson, B.O. 2004. Reconstruction and validation of Saccharomyces cerevisiae iND750, a fully compartmentalized genome-scale metabolic model. Genome Res. 14, 1298-1309.
6. Forster, J., Famili, I., Fu, P., et al. 2003. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network. Genome Res. 13, 244-253.
7. Giaever, G., Chu, A.M., Ni, L., et al. 2002. Functional profiling of the Saccharomyces cerevisiae genome. Nature 418, 387-391.
8. Kaufman, D.E., and Smith, R.L. 1998. Direction choice for accelerated convergence in hit-and-run sampling. Oper. Res. 46, 84-95.
9. Kelley, R., and Ideker, T. 2005. Systematic interpretation of genetic interactions using protein networks. Nat. Biotechnol. 23, 561-566.
10. Lee, D.S., Park, J., Kay, K.A., et al. 2008. The implications of human metabolic network topology for disease comorbidity. Proc. Natl. Acad. Sci. USA 105, 9880-9885.
11. McKusick, V.A. 2007. Mendelian inheritance in man and its online version, OMIM. Am. J. Hum. Genet. 80, 588-604.
12. Nakamura, H., Miura, K., Fukuda, Y., et al. 2000. Phosphatidylserine synthesis required for the maximal tryptophan transport activity in Saccharomyces cerevisiae. Biosci. Biotechnol. Biochem. 64, 167-172.
13. Nyhan, W.L., James, J.A., Teberg, A.J., et al. 1969. A new disorder of purine metabolism with behavioral manifestations. J. Pediatr. 74, 20-27.
14. Pan, X., Yuan, D.S., Xiang, D., et al. 2004. A robust toolkit for functional profiling of the yeast genome. Mol. Cell 16, 487-496.
15. Price, N.D., Reed, J.L., and Palsson, B.O. 2004a. Genome-scale models of microbial cells: evaluating the consequences of constraints. Nat. Rev. Microbiol. 2, 886-897.
16. Price, N.D., Schellenberger, J., and Palsson, B.O. 2004b. Uniform sampling of steady-state flux spaces: means to design experiments and to interpret enzymopathies. Biophys. J. 87, 2172-2186.
17. Savinell, J.M., and Palsson, B.O. 1992. Optimal selection of metabolic fluxes for in vivo measurement. II. Application to Escherichia coli and hybridoma cell metabolism. J. Theor. Biol. 155, 215-242.
18. Schuldiner, M., Collins, S.R., Thompson, N.J., et al. 2005. Exploration of the function and organization of the yeast early secretory pathway through an epistatic miniarray profile. Cell 123, 507-519.
19. Segre, D., Deluna, A., Church, G.M., et al. 2005. Modular epistasis in yeast metabolism. Nat. Genet. 37, 77-83.
20. Shannon, P., Markiel, A., Ozier, O., et al. 2003. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498-2504.
21. Sing, T., Sander, O., Beerenwinkel, N., et al. 2005. ROCR: visualizing classifier performance in R. Bioinformatics 21, 3940-3941.
22. Song, S., and Friedmann, T. 2007. Tissue-specific aberrations of gene expression in HPRT-deficient mice: functional complexity in a monogenic disease? Mol. Ther. 15, 1432-1443.
23. Stark, C., Breitkreutz, B.J., Reguly, T., et al. 2006. BioGRID: a general repository for interaction datasets. Nucleic Acids Res. 34, D535-D539.
24. Thiele, I., Price, N.D., Vo, T.D., et al. 2005. Candidate metabolic network states in human mitochondria. Impact of diabetes, ischemia, and diet. J. Biol. Chem. 280, 11683-11695.
25. Tong, A.H., Lesage, G., Bader, G.D., et al. 2004. Global mapping of the yeast genetic interaction network. Science 303, 808-813.
26. Ulitsky, I., and Shamir, R. 2007. Pathway redundancy and protein essentiality revealed in the Saccharomyces cerevisiae interaction networks. Mol. Syst. Biol. 3, 104.
27. van Driel, M.A., Bruggeman, J., Vriend, G., et al. 2006. A text-mining analysis of the human phenome. Eur. J. Hum. Genet. 14, 535-542.
28. Waterham, H.R. 2002. Inherited disorders of cholesterol biosynthesis. Clin. Genet. 61, 393-403.
29. Wu, X., Jiang, R., Zhang, M.Q., et al. 2008. Network-based global inference of human disease genes. Mol. Syst. Biol. 4, 189.
30. Ye, P., Peyser, B.D., Pan, X., et al. 2005. Gene function prediction from congruent synthetic lethal interactions in yeast. Mol. Syst. Biol. 1, 2005.0026.