Per request from meta comment.

I am self-learning about whole cell modeling, specifically An introduction to whole-cell modeling and Fundamentals of Systems Biology: From Synthetic Circuits to Whole-cell Models. While my background is decades of programming, for cellular biology it is only skimming through a few books.

In the process of learning I soon discovered software/apps that use SBML (System Biology Markup language) but in referring back to "An introduction to whole-cell modeling" see that they use BioNetGen (GitHub) which has its own language BioNetGen language (BNGL)

What are the differences between BNGL (BioNetGen Language) and SBML (System Biology Markup Langague) formats?


Both formats have formal grammars for describing similar concepts, however they are different and to my knowledge one is not a proper subset of the other. While one could do a comparison of a syntactic nature, a simple Google search of just both acronyms reveals BioNetGen 2.2: Advances in Rule-Based Modeling

In here can be found:

2.4 SBML-to-BNGL translation
SBML is a widely-used model exchange format in systems biology (Hucka et al., 2003). Models encoded in SBML are flat, i.e., their species do not have internal structure, which limits their utility for rule-based modeling. BioNetGen 2.2 includes an SBML-to-BNGL translator, called Atomizer (also available as a web tool at ratomizer.appspot.com), that can extract implicit molecular structure from flat species (Tapia and Faeder, 2013). A full report on Atomizer and its application to the BioModels database (Li et al., 2010) is currently in preparation. However, Tapia and Faeder (2013) reported that an early version of the tool could recover implicit structure for about 60% of species in models within the database that contain ≥20 species. Thus, Atomizer makes available a large set of pre-existing models in a rule-based format, facilitating their visualization (Wenskovitch et al., 2014) and extension (Chylek et al., 2015).

While not directly related to the question this also helped in understanding more about BioNetGen

Wikipedia: Multi-state modeling of biomolecules

Biological signaling systems often rely on complexes of biological macromolecules that can undergo several functionally significant modifications that are mutually compatible. Thus, they can exist in a very large number of functionally different states. Modeling such multi-state systems poses two problems: The problem of how to describe and specify a multi-state system (the "specification problem") and the problem of how to use a computer to simulate the progress of the system over time (the "computation problem"). To address the specification problem, modelers have in recent years moved away from explicit specification of all possible states, and towards rule-based formalisms that allow for implicit model specification, including the κ-calculus, BioNetGen, the Allosteric Network Compiler and others. To tackle the computation problem, they have turned to particle-based methods that have in many cases proved more computationally efficient than population-based methods based on ordinary differential equations, partial differential equations, or the Gillespie stochastic simulation algorithm. Given current computing technology, particle-based methods are sometimes the only possible option. Particle-based simulators further fall into two categories: Non-spatial simulators such as StochSim, DYNSTOC, RuleMonkey, and NFSim and spatial simulators, including Meredys, SRSim and MCell. Modelers can thus choose from a variety of tools; the best choice depending on the particular problem. Development of faster and more powerful methods is ongoing, promising the ability to simulate ever more complex signaling processes in the future.

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    $\begingroup$ Answering your own question immediately is not frowned upon. you have the option since you ask! But is usually recommended to not accept an answer between minutes of asking it. $\endgroup$
    – llrs
    Feb 21 '18 at 15:48
  • $\begingroup$ It would help tremendously if this were written and formatted as a proper answer rather than a meta-discussion. $\endgroup$ Feb 21 '18 at 15:50
  • $\begingroup$ @KonradRudolph I edited both Q and A, but you can improve them further :D in case I missed something $\endgroup$
    – llrs
    Feb 21 '18 at 15:50
  • $\begingroup$ I have still to read the sources, but I hope so. Thanks (+1) for sharing your knowledge. One more thing, in case you cite a paper, usually is better to cite the peer-reviewed and accepted paper if possible. $\endgroup$
    – llrs
    Feb 21 '18 at 16:04

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