Flexible informatics for linking experimental data to mathematical models via DataRail

Motivation: Linking experimental data to mathematical models in biology is impeded by the lack of suitable software to manage and transform data. Model calibration would be facilitated and models would increase in value were it possible to preserve links to training data along with a record of all n...

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Veröffentlicht in:Bioinformatics Jg. 24; H. 6; S. 840 - 847
Hauptverfasser: Saez-Rodriguez, Julio, Goldsipe, Arthur, Muhlich, Jeremy, Alexopoulos, Leonidas G., Millard, Bjorn, Lauffenburger, Douglas A., Sorger, Peter K.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Oxford Oxford University Press 15.03.2008
Oxford Publishing Limited (England)
Schlagworte:
Algorithms
Bioinformatics
Biological and medical sciences
Computational Biology - methods
Computer Simulation
Database Management Systems
Databases, Protein
Experimental data
Fundamental and applied biological sciences. Psychology
General aspects
Information Storage and Retrieval - methods
Mathematical models
Mathematics in biology. Statistical analysis. Models. Metrology. Data processing in biology (general aspects)
Models, Biological
Programming Languages
Proteome - metabolism
Research Design
Software
Mathematical model
Bioinformatics
Experimental data
ISSN:1367-4803, 1367-4811, 1460-2059, 1367-4811
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Zusammenfassung:Motivation: Linking experimental data to mathematical models in biology is impeded by the lack of suitable software to manage and transform data. Model calibration would be facilitated and models would increase in value were it possible to preserve links to training data along with a record of all normalization, scaling, and fusion routines used to assemble the training data from primary results. Results: We describe the implementation of DataRail, an open source MATLAB-based toolbox that stores experimental data in flexible multi-dimensional arrays, transforms arrays so as to maximize information content, and then constructs models using internal or external tools. Data integrity is maintained via a containment hierarchy for arrays, imposition of a metadata standard based on a newly proposed MIDAS format, assignment of semantically typed universal identifiers, and implementation of a procedure for storing the history of all transformations with the array. We illustrate the utility of DataRail by processing a newly collected set of ∼22 000 measurements of protein activities obtained from cytokine-stimulated primary and transformed human liver cells. Availability: DataRail is distributed under the GNU General Public License and available at http://code.google.com/p/sbpipeline/ Contact: sbpipeline@hms.harvard.edu Supplementary information: Supplementary data are available at Bioinformatics online.
Bibliographie:To whom correspondence should be addressed.
Associate Editor: Trey Ideker
ArticleID:btn018
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Contact: sbpipeline@hms.harvard.edu
Associate Editor: Dr. Trey Ideker
The first two authors contributed equally to this work.
ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btn018