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This article is part of the supplement: Validation methods for functional genome annotation

Open Access Research

Genome-wide functional annotation and structural verification of metabolic ORFeome of Chlamydomonas reinhardtii

Lila Ghamsari12, Santhanam Balaji12, Yun Shen12, Xinping Yang12, Dawit Balcha12, Changyu Fan12, Tong Hao12, Haiyuan Yu3*, Jason A Papin4* and Kourosh Salehi-Ashtiani125*

Author Affiliations

1 Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02115, USA

2 Department of Genetics, Harvard Medical School, Boston, MA 02115, USA

3 Department of Biological Statistics and Computational Biology and Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA

4 Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA

5 New York University Abu Dhabi, Abu Dhabi, UAE, and Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA

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BMC Genomics 2011, 12(Suppl 1):S4  doi:10.1186/1471-2164-12-S1-S4

Published: 15 June 2011

Additional files

Additional File 1:

JGIv4.0 gene model names, their predicted sequence, EC annotation, and verification status of their structural annotation.

Format: XLS Size: 2.4MB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional File 2:

Subcellular localization prediction of JGI v4.0 enzymes predicted by WoLF PSORT as plant or animal proteins.

Format: XLS Size: 252KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data

Additional File 3:

A consolidated set of high confidence subcellular localization predictions made by WoLF PSORT. Subcellular compartments predicted for JGI v4.0 as plant or animal at 0.85 or higher ratio relative to other compartments were selected then consolidated by reporting the prediction with the higher value.

Format: XLS Size: 61KB Download file

This file can be viewed with: Microsoft Excel Viewer

Open Data