MetRxn: a knowledgebase of metabolites and reactions spanning metabolic models and databases |
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Authors: | Akhil Kumar Patrick F Suthers Costas D Maranas |
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Institution: | 1.Department of Computer Science,The Pennsylvania State University,USA;2.Department of Chemical Engineering,The Pennsylvania State University,USA |
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Abstract: | Background Increasingly, metabolite and reaction information is organized in the form of genome-scale metabolic reconstructions that
describe the reaction stoichiometry, directionality, and gene to protein to reaction associations. A key bottleneck in the
pace of reconstruction of new, high-quality metabolic models is the inability to directly make use of metabolite/reaction
information from biological databases or other models due to incompatibilities in content representation (i.e., metabolites
with multiple names across databases and models), stoichiometric errors such as elemental or charge imbalances, and incomplete
atomistic detail (e.g., use of generic R-group or non-explicit specification of stereo-specificity). |
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Keywords: | |
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