The DOI matches its Crossref record; 66 of the 66 references it cites were found in a registry or an index.
Global phenotypic characterization of bacteria
Open accessAbstract
The measure of the quality of a systems biology model is how well it can reproduce and predict the behaviors of a biological system such as a microbial cell. In recent years, these models have been built up in layers, and each layer has been growing in sophistication and accuracy in parallel with a global data set to challenge and validate the models in predicting the content or activities of genes (genomics), proteins (proteomics), metabolites (metabolomics), and ultimately cell phenotypes (phenomics). This review focuses on the latter, the phenotypes of microbial cells. The development of Phenotype MicroArrays, which attempt to give a global view of cellular phenotypes, is described. In addition to their use in fleshing out and validating systems biology models, there are many other uses of this global phenotyping technology in basic and applied microbiology research, which are also described.
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Cites
High resolution two-dimensional electrophoresis of proteins.
O'Farrell, P. (1975) · Journal of Biological Chemistry · doi:10.1016/s0021-9258(19)41496-8 · Cited by 19,246
One-step inactivation of chromosomal genes in Escherichia coli K-12 using PCR products
Datsenko, K. A., & Wanner, B. L. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.120163297 · Cited by 14,782
The Minimal Gene Complement of Mycoplasma genitalium
Fraser, C. M., Gocayne, J. D., White, O., Adams, M. D., Clayton, R. A., Fleischmann, R. D., Bult, C. J., Kerlavage, A. R., Sutton, G., Kelley, J. M., et al. (1995) · Science · doi:10.1126/science.270.5235.397 · Cited by 2,545
Listeria Pathogenesis and Molecular Virulence Determinants
Vázquez-Boland, J. A., Kuhn, M., Berche, P., Chakraborty, T., Domı́nguez-Bernal, G., Goebel, W., González-Zorn, B., Wehland, J., & Kreft, J. (2001) · Clinical Microbiology Reviews · doi:10.1128/cmr.14.3.584-640.2001 · Cited by 2,152
Feist, A. M., Henry, C. S., Reed, J. L., Krummenacker, M., Joyce, A. R., Karp, P. D., Broadbelt, L. J., Hatzimanikatis, V., & Palsson, B. Ø. (2007) · Molecular Systems Biology · doi:10.1038/msb4100155 · Cited by 1,383
Mg2+ as an Extracellular Signal: Environmental Regulation of Salmonella Virulence
Véscovi, E. G., Soncini, F. C., & Groisman, E. A. (1996) · Cell · doi:10.1016/s0092-8674(00)81003-x · Cited by 841
Regulation of secondary metabolism in streptomycetes
Bibb, M. J. (2005) · Current Opinion in Microbiology · doi:10.1016/j.mib.2005.02.016 · Cited by 821
Integrating high-throughput and computational data elucidates bacterial networks
Covert, M. W., Knight, E. M., Reed, J. L., Herrgard, M. J., & Palsson, B. O. (2004) · Nature · doi:10.1038/nature02456 · Cited by 792
Environmental signals controlling expression of virulence determinants in bacteria
Mekalanos, J. J. (1992) · Journal of Bacteriology · doi:10.1128/jb.174.1.1-7.1992 · Cited by 788
Multiplexed biochemical assays with biological chips
Fodor, S. P. A., Rava, R. P., Huang, X. C., Pease, A. C., Holmes, C. P., & Adams, C. L. (1993) · Nature · doi:10.1038/364555a0 · Cited by 731
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KBase: The United States Department of Energy Systems Biology Knowledgebase
(2018) · doi:10.1038/nbt.4163 · Cited by 1,624
High-throughput generation, optimization and analysis of genome-scale metabolic models
Henry, C. S., DeJongh, M., Best, A. A., Frybarger, P. M., Linsay, B., & Stevens, R. L. (2010) · Nature Biotechnology · doi:10.1038/nbt.1672 · Cited by 1,090
Kostka, J. E., Prakash, O., Overholt, W. A., Green, S. J., Freyer, G., Canion, A., Delgardio, J., Norton, N., Hazen, T. C., & Huettel, M. (2011) · Applied and Environmental Microbiology · doi:10.1128/aem.05402-11 · Cited by 875
Pathway Tools version 13.0: integrated software for pathway/genome informatics and systems biology
Karp, P. D., Paley, S. M., Krummenacker, M., Latendresse, M., Dale, J. M., Lee, T. J., Kaipa, P., Gilham, F., Spaulding, A., Popescu, L., et al. (2010) · Briefings in Bioinformatics · doi:10.1093/bib/bbp043 · Cited by 694
ScanLag: High-throughput Quantification of Colony Growth and Lag Time
Levin-Reisman, I., Fridman, O., & Balaban, N. Q. (2014) · Journal of Visualized Experiments · doi:10.3791/51456 · Cited by 64
Metadata
- Authors
- Bochner, B. R.
- Venue
- FEMS Microbiology Reviews
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-01
- Volume
- 33
- Issue
- 1
- Pages
- 191-205
- ISSN
- 0168-6445 (ISSN-L)
- 1574-6976
- OpenAlex
- W1966614672
- Cited by
- 440
- References
- 66
- FWCI
- 7.82
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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