Brief Communication abstract

Nature Methods 6, 589 - 592 (2009)
Published online: 13 July 2009 | Corrected online: 20 July 2009 | doi:10.1038/nmeth.1348

Metabolic network analysis integrated with transcript verification for sequenced genomes

Ani Manichaikul1,6, Lila Ghamsari2,6, Erik F Y Hom3,6, Chenwei Lin2,6, Ryan R Murray2,6, Roger L Chang4,6, S Balaji2, Tong Hao2, Yun Shen2, Arvind K Chavali1, Ines Thiele4,5, Xinping Yang2, Changyu Fan2, Elizabeth Mello2, David E Hill2, Marc Vidal2, Kourosh Salehi-Ashtiani2 & Jason A Papin1


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.

  1. Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.
  2. Center for Cancer Systems Biology and Department of Cancer Biology, Dana-Farber Cancer Institute, and Department of Genetics, Harvard Medical School, Boston, Massachusetts, USA.
  3. Department of Molecular and Cellular Biology, Harvard University, Cambridge, Massachusetts, USA.
  4. Department of Bioengineering, University of California, San Diego, La Jolla, California, USA.
  5. Present address: Center for Systems Biology, University of Iceland, Reykjavik, Iceland.
  6. These authors contributed equally to this work.

Correspondence to: Kourosh Salehi-Ashtiani2 e-mail:

Correspondence to: Jason A Papin1 e-mail:

* In the version of this article initially published online, the email address of one of the Corresponding authors was spelled incorrectly. The correct email address is e-mail: The error has been corrected for the print, PDF and HTML versions of this article.


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