Skip Navigation

This Article
Right arrow FREE Full Text (Print PDF) Freely available
Right arrow FREE Full Text (Screen PDF)
Right arrow Comments: Submit a response
Right arrow Alert me when this article is cited
Right arrow Alert me when Comments are posted
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrowRequest Permissions
Google Scholar
Right arrow Articles by Kharchenko, P.
Right arrow Articles by Church, G. M.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Kharchenko, P.
Right arrow Articles by Church, G. M.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Bioinformatics 20(Suppl. 1) © Oxford University Press 2004; all rights reserved.

Filling gaps in a metabolic network using expression information

Peter Kharchenko {dagger}, Dennis Vitkup {dagger} and George M. Church *

Department of Genetics, Harvard Medical School, 77 Louis Pasteur Avenue Boston, MA 02115, USA

Received on January 15, 2004; accepted on March 1, 2004

Motivation: The metabolic models of both newly sequenced and well-studied organisms contain reactions for which the enzymes have not been identified yet. We present a computational approach for identifying genes encoding such missing metabolic enzymes in a partially reconstructed metabolic network.

Results: The metabolic expression placement (MEP) method relies on the coexpression properties of the metabolic network and is complementary to the sequence homology and genome context methods that are currently being used to identify missing metabolic genes. The MEP algorithm predicts over 20% of all known Saccharomyces cerevisiae metabolic enzyme-encoding genes within the top 50 out of 5594 candidates for their enzymatic function, and 70% of metabolic genes whose expression level has been significantly perturbed across the conditions of the expression dataset used.

Availability: Freely available (in Supplementary information).

Supplementary information: Available at the following URL http://arep.med.harvard.edu/kharchenko/mep/supplements.html

Contact: g1m1c1{at}arep.med.harvard.edu

* To whom correspondence should be addressed.

{dagger} The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?


This article has been cited by other articles:


Home page
 BioinformaticsHome page
K. Faust, D. Croes, and J. van Helden
In response to 'Can sugars be produced from fatty acids? A test case for pathway analysis tools'
Bioinformatics, December 1, 2009; 25(23): 3202 - 3205.
[Abstract] [Full Text] [PDF]

Home page
 J. Bacteriol.Home page
N. E. Lewis, B.-K. Cho, E. M. Knight, and B. O. Palsson
Gene Expression Profiling and the Use of Genome-Scale In Silico Models of Escherichia coli for Analysis: Providing Context for Content
J. Bacteriol., June 1, 2009; 191(11): 3437 - 3444.
[Full Text] [PDF]


Disclaimer: Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.