Open Access Highly Accessed Methodology article

Improving metabolic flux predictions using absolute gene expression data

Dave Lee1, Kieran Smallbone1, Warwick B Dunn1, Ettore Murabito1, Catherine L Winder1, Douglas B Kell12, Pedro Mendes13 and Neil Swainston1*

Author Affiliations

1 Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester, M1 7DN, UK

2 School of Chemistry, University of Manchester, Manchester, M13 9PL, UK

3 Virginia Bioinformatics Institute, Virginia Tech, Washington St. 0477, Blacksburg, Virginia, 24060, USA

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BMC Systems Biology 2012, 6:73  doi:10.1186/1752-0509-6-73

Published: 19 June 2012

Additional files

Additional file 1:

Exometabolomics data. Experimentally measured exometabolomic flux data, both unscaled and carbon-scaled. Data generated from cellular culture grown at both 75% and 85% maximum biomass level, in units of mmoles/hr/g dry weight. (XLS 37 kb)

Format: XLS Size: 38KB Download file

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Additional file 2:

Yeast 5.Genome-scale metabolic model of metabolism in Saccharomyces cerevisiae.

Format: XML Size: 4.4MB Download file

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Additional file 3:

Gene data 75%.Gene expression data, generated by RNA-Seq, on cellular culture grown at 75% maximum biomass level, in units of reads per kilobase of transcript per million mapped reads (RPKM).

Format: TXT Size: 172KB Download file

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Additional file 4:

Gene data 85%.Gene expression data, generated by RNA-Seq, on cellular culture grown at 85% maximum biomass level, in units of RPKM.

Format: TXT Size: 172KB Download file

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Additional file 5:

Results.Matlab script that runs the analysis function, using the above model and gene expression data. Generates flux predictions and compares these to the above experimentally measured exometabolomic flux data.

Format: M Size: 2KB Download file

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Additional file 6:

Analysis.Matlab function that performs the method described in this work. Additionally provides implementations of the existing algorithms GIMME [18] and iMAT [14].

Format: M Size: 12KB Download file

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Additional file 7:

Gene expression mapper for enzymatic complexes (A and B).Helper Matlab function that is used in mapping gene expression data to individual reactions. Called by analysis function.

Format: M Size: 1KB Download file

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Additional file 8:

Gene expression mapper for isoenzymes (A or B).Helper Matlab function that is used in mapping gene expression data to individual reactions. Called by analysis function.

Format: M Size: 1KB Download file

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