RAM: An annotation standard for SBML Level 3. Specification Documents
Metabolic networks with gene expression are researched under very different banners with different techniques. For example, there are the dynamic enzyme-cost Flux Balance Analysis (deFBA) , conditional Flux Balance Analysis , Metabolism and Expression models (ME models) , Resource Balance Analysis , etc. At their core, these methods can all understood as Resource Allocation Models (RAM) and while investigating their potential and their results, we encountered the problem of sharing these types of models between workgroups. The usual goto-standard is the Systems Biology Markup Language (SBML) but even with the latest available packages some resource allocation model parameters cannot be integrated.
Thus, we have developed the 'ram'-standard, which utilizes the <annotation> field available inside the species and reactions element to solve this problem. Naturally, the standard includes a few more conventions for describing RAM. This document contains all these specifications.
You can use the latest version of libsbml (version >5.13)  and directly use the 'ram' standard without additional software. At the moment we support interfaces from 'ram' to a Python implementation () and a MATLAB implementation (link). Below you can also find a few examples of models in the 'ram' format.
In this first version we focused on the parameters needed for deFBA models, but we hope to support more model types in the near future. If you want to contribute, you can do so via the issue manager of the bitbucket copy of the specifications .
 Waldherr, S.; Oyarzún, D.A.; Bockmayr, A. Dynamic optimization of metabolic networks coupled with gene expression. Journal of Theoretical Biology 2015, 365, 469–485.
 Reimers, A.M.; Knoop, H.; Bockmayr, A.; Steuer, R. Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth. Proceedings of the National Academy of Sciences 2017 (in press).
 Lerman, J.A.; Hyduke, D.R.; Latif, H.; Portnoy, V.A.; others. In silico method for modelling metabolism and gene product expression at genome scale. Nature Communications 2012.
 Goelzer, A.; Fromion, V.; Scorletti, G. Cell design in bacteria as a convex optimization problem. Automatica 2011, 47, 1210–1218
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Created: 7th Jul 2017 at 11:02
Last updated: 21st Sep 2017 at 14:03
Last used: 20th Oct 2017 at 10:34