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Prediction and Characterization of Missing Proteomic Data in Desulfovibrio vulgaris
Proteomic datasets are often incomplete due to identification range and sensitivity issues. It becomes important to develop methodologies to estimate missing proteomic data, allowing better interpretation of proteomic datasets and metabolic mechanisms underlying complex biological systems. In this s...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Hindawi Publishing Corporation
2011
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3114432/ https://www.ncbi.nlm.nih.gov/pubmed/21687592 http://dx.doi.org/10.1155/2011/780973 |