PySB

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PySB
Initial releaseMay 15, 2019; 5 years ago (2019-05-15)
Stable release
1.14 / August 29, 2022; 22 months ago (2022-08-29)
Written inPython
Operating systemLinux, macOS and Microsoft Windows
PlatformPython
LicenseBSD License
Websitepysb.org

PySB

PySB.[1] is a Python-based open-source simulator for cellular systems developed by Carlos Lopez. The primary capability of pySB than makes it stand out from other similar simulators is that it supports rule-based modeling[2]. The software runs on all major platforms, Windows, Mac OS, and Linux. PySB is also discussed at Multi-state modeling of biomolecules.

Capabilities[3]

  • Can be used to describe rule-based models of complex biochemical pathways, particularly signaling pathways.
  • Can be used to create model libraries based on macros to reuse.
  • Uses standard python sci-py numerical libraries for carrying out simulations.

Applications of pySB

pySB has been used in a variety of research projects. The following lists a small number of those studies (out of a total of 230 mentions in the scientific literature (as of Oct 2022).

  • Studies on substrate selectivity in cyclooxygenase-2[4]
  • Information discrimination in T-cell signaling[5]
  • Modeling of JNK3 cascade[6]
  • Inverted control of eukaryotic gene expression[7]
  • Construction of Cellular Responses and Global Drug Mechanisms of Action[8]

These have all been impactful studies (Google Scholar) and indicate that pySB is being used in a variety of important research areas.

Notability

There are a number of distinguishing features of pySB that make it standout from other simular cellular modeling platforms:

  • PySB is the only python-based simulation package for systems biology that supports rule-based modeling.
  • PySB can translate BioNetGen[9] and Kappa[10] rules into its own rule-based language.
  • PySB also allows users to divide models into modules and to call libraries of reusable elements (macros) that encode standard biochemical actions.

A number of reviews and commentaries have been written that discuss pySB:

  • Slater[11]. describes in detail the pros and cons of a variety of rule-based languages and platforms, including pySB
  • Mitra and Hlaveck[12] briefly discuss the importance of pySB, where they state: "Another package of note is PySB which has support for BNGL"
  • Chicklet et al[13], discuss at length a variety of rule-based modeling platforms but particularly pySB.

SBML Support

pySB is able to export SBML in flattened form[14]. That is, the rule-based model is converted into explicit reactions. This means that the rule-based formalism is not preserved.

For import, pySB converts the SBML into BioNetGen first using BioNetGen application. pySB then imports the BioNetGen format using the pySB BioNetGen importer. This means import is limited by the import capabilities of BioNetGen[15].

See also

  • List of systems biology modeling software

References

  1. Lopez, Carlos F; Muhlich, Jeremy L; Bachman, John A; Sorger, Peter K (January 2013). "Programming biological models in Python using PySB". Molecular Systems Biology 9 (1): 646. doi:10.1038/msb.2013.1. 
  2. Chylek, Lily A.; Harris, Leonard A.; Tung, Chang‐Shung; Faeder, James R.; Lopez, Carlos F.; Hlavacek, William S. (January 2014). "Rule‐based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems". WIREs Systems Biology and Medicine 6 (1): 13–36. doi:10.1002/wsbm.1245. 
  3. "readthedocs for pysb". https://pysb.readthedocs.io/en/stable/. 
  4. Mitchener, Michelle M.; Hermanson, Daniel J.; Shockley, Erin M.; Brown, H. Alex; Lindsley, Craig W.; Reese, Jeff; Rouzer, Carol A.; Lopez, Carlos F. et al. (6 October 2015). "Competition and allostery govern substrate selectivity of cyclooxygenase-2". Proceedings of the National Academy of Sciences 112 (40): 12366–12371. doi:10.1073/pnas.1507307112. 
  5. Ganti, Raman S.; Lo, Wan-Lin; McAffee, Darren B.; Groves, Jay T.; Weiss, Arthur; Chakraborty, Arup K. (20 October 2020). "How the T cell signaling network processes information to discriminate between self and agonist ligands". Proceedings of the National Academy of Sciences 117 (42): 26020–26030. doi:10.1073/pnas.2008303117. 
  6. Perry, Nicole A.; Kaoud, Tamer S.; Ortega, Oscar O.; Kaya, Ali I.; Marcus, David J.; Pleinis, John M.; Berndt, Sandra; Chen, Qiuyan et al. (15 January 2019). "Arrestin-3 scaffolding of the JNK3 cascade suggests a mechanism for signal amplification". Proceedings of the National Academy of Sciences 116 (3): 810–815. doi:10.1073/pnas.1819230116. 
  7. Park, Heungwon; Subramaniam, Arvind R. (18 September 2019). "Inverted translational control of eukaryotic gene expression by ribosome collisions". PLOS Biology 17 (9): e3000396. doi:10.1371/journal.pbio.3000396. 
  8. Norris, Jeremy L.; Farrow, Melissa A.; Gutierrez, Danielle B.; Palmer, Lauren D.; Muszynski, Nicole; Sherrod, Stacy D.; Pino, James C.; Allen, Jamie L. et al. (3 March 2017). "Integrated, High-Throughput, Multiomics Platform Enables Data-Driven Construction of Cellular Responses and Reveals Global Drug Mechanisms of Action". Journal of Proteome Research 16 (3): 1364–1375. doi:10.1021/acs.jproteome.6b01004. 
  9. Blinov, M. L.; Faeder, J. R.; Goldstein, B.; Hlavacek, W. S. (22 November 2004). "BioNetGen: software for rule-based modeling of signal transduction based on the interactions of molecular domains". Bioinformatics 20 (17): 3289–3291. doi:10.1093/bioinformatics/bth378. 
  10. Boutillier, Pierre; Maasha, Mutaamba; Li, Xing; Medina-Abarca, Héctor F; Krivine, Jean; Feret, Jérôme; Cristescu, Ioana; Forbes, Angus G et al. (1 July 2018). "The Kappa platform for rule-based modeling". Bioinformatics 34 (13): i583–i592. doi:10.1093/bioinformatics/bty272. 
  11. Slater, Ted (February 2014). "Recent advances in modeling languages for pathway maps and computable biological networks". Drug Discovery Today 19 (2): 193–198. doi:10.1016/j.drudis.2013.12.011. 
  12. Mitra, Eshan D.; Hlavacek, William S. (December 2019). "Parameter estimation and uncertainty quantification for systems biology models". Current Opinion in Systems Biology 18: 9–18. doi:10.1016/j.coisb.2019.10.006. 
  13. Chylek, Lily A.; Harris, Leonard A.; Tung, Chang‐Shung; Faeder, James R.; Lopez, Carlos F.; Hlavacek, William S. (January 2014). "Rule‐based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems". WIREs Systems Biology and Medicine 6 (1): 13–36. doi:10.1002/wsbm.1245. 
  14. "pySB Export". https://pysb.readthedocs.io/en/stable/modules/export/index.html. 
  15. "pySB Import". https://pysb.readthedocs.io/en/stable/modules/importers/index.html. 

External links

Category:Systems biology Category:Ordinary differential equations Category:Software using the BSD license



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