| pubmed-article:18793442 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:18793442 | lifeskim:mentions | umls-concept:C0007634 | lld:lifeskim |
| pubmed-article:18793442 | lifeskim:mentions | umls-concept:C0085470 | lld:lifeskim |
| pubmed-article:18793442 | lifeskim:mentions | umls-concept:C0311400 | lld:lifeskim |
| pubmed-article:18793442 | lifeskim:mentions | umls-concept:C0524865 | lld:lifeskim |
| pubmed-article:18793442 | lifeskim:mentions | umls-concept:C0442614 | lld:lifeskim |
| pubmed-article:18793442 | pubmed:dateCreated | 2008-10-20 | lld:pubmed |
| pubmed-article:18793442 | pubmed:abstractText | Pseudomonas putida is the best studied pollutant degradative bacteria and is harnessed by industrial biotechnology to synthesize fine chemicals. Since the publication of P. putida KT2440's genome, some in silico analyses of its metabolic and biotechnology capacities have been published. However, global understanding of the capabilities of P. putida KT2440 requires the construction of a metabolic model that enables the integration of classical experimental data along with genomic and high-throughput data. The constraint-based reconstruction and analysis (COBRA) approach has been successfully used to build and analyze in silico genome-scale metabolic reconstructions. | lld:pubmed |
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| pubmed-article:18793442 | pubmed:language | eng | lld:pubmed |
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| pubmed-article:18793442 | pubmed:citationSubset | IM | lld:pubmed |
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| pubmed-article:18793442 | pubmed:chemical | http://linkedlifedata.com/r... | lld:pubmed |
