Flexible informatics for linking experimental data to mathematical models via DataRail.
BACKGROUND
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 approximately 22 000 measurements of protein activities obtained from cytokine-stimulated primary and transformed human liver cells.


BACKGROUND
DataRail is distributed under the GNU General Public License and available at http://code.google.com/p/sbpipeline/
Saez-Rodriguez
Julio
J
Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.
Goldsipe
Arthur
A
Muhlich
Jeremy
J
Alexopoulos
Leonidas G
LG
Millard
Bjorn
B
Lauffenburger
Douglas A
DA
Sorger
Peter K
PK
D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D003628:Database Management Systems; D030562:Databases, Protein; D016247:Information Storage and Retrieval / Q000379:methods; D008954:Models, Biological; D011381:Programming Languages; D020543:Proteome / Q000378:metabolism*; D012107:Research Design; D012984:Software
D020543:Proteome