Metabolic network analysis integrated with transcript verification for sequenced genomes

Ani Manichaikul, Lila Ghamsari, Erik F.Y. Hom, Chenwei Lin, Ryan R. Murray, Roger L. Chang, S. Balaji, Tong Hao, Yun Shen, Arvind K. Chavali, Ines Thiele, Xinping Yang, Changyu Fan, Elizabeth Mello, David E. Hill, Marc Vidal, Kourosh Salehi-Ashtiani, Jason A. Papin

Research output: Contribution to journalArticle

Abstract

With sequencing of thousands of organisms completed or in progress, there is a growing need to integrate gene prediction with metabolic network analysis. Using Chlamydomonas reinhardtii as a model, we describe a systems-level methodology bridging metabolic network reconstruction with experimental verification of enzyme encoding open reading frames. Our quantitative and predictive metabolic model and its associated cloned open reading frames provide useful resources for metabolic engineering.

Original languageEnglish (US)
Pages (from-to)589-592
Number of pages4
JournalNature methods
Volume6
Issue number8
DOIs
StatePublished - Jul 14 2009

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ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology

Cite this

Manichaikul, A., Ghamsari, L., Hom, E. F. Y., Lin, C., Murray, R. R., Chang, R. L., Balaji, S., Hao, T., Shen, Y., Chavali, A. K., Thiele, I., Yang, X., Fan, C., Mello, E., Hill, D. E., Vidal, M., Salehi-Ashtiani, K., & Papin, J. A. (2009). Metabolic network analysis integrated with transcript verification for sequenced genomes. Nature methods, 6(8), 589-592. https://doi.org/10.1038/nmeth.1348