Difference between revisions of "Tools Comparison 2022"

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!colspan="9"|'''Standards'''
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!colspan="9"|'''Systems Biology Markup Language'''
 
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|1. SBML
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|1. level and version
| l3v2, all tests passed
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| l3v2 (all tests passed)
 
| l3v2 except<br>algebraic
 
| l3v2 except<br>algebraic
 
| l3v2
 
| l3v2
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| l3v2 except<br>algebraic, delay
 
| l3v2 except<br>algebraic, delay
 
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|2. SBML comp
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|3. comp package
 
| fully, all tests passed
 
| fully, all tests passed
 
| import
 
| import
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| partially
 
| partially
 
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|3. SBML fbc
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|4. fbc package
 
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|3. SBML arrays
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|5. arrays package
 
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|3. SBML layout
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|6. layout package
 
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|4. SBGN PD
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!colspan="9"|'''Other Standards'''
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|1. SBGN PD
 
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| +
 
| export
 
| export
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|5. SBGN-ML
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|2. SBGN-ML
 
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|6. SedML
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|3. SedML
 
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|7. Combine archive
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|4. Combine archive
 
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|8. SBOL
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|5. SBOL
 
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|9. Antimony
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|6. Antimony
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|10. Bionetgen
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|7. Bionetgen
 
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|11. BioPAX
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|8. BioPAX
 
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Revision as of 02:36, 19 March 2022

Here we collect information about similar software and their features in comparison with BioUML.

Comparisons made by third parties

  • Support of SBML standard can be measured by percentage of passed tests from test suite presented on SBML web site.
  • Extensive comparison of different simulators according to their speed and percentage of passed SBML tests was performed by Maggioli et al.[1]

Modeling tools comparison

This comparison was made in February 2022. Previous was done in 2019 and is available at separate page Tools Comparison.

BioUML [2] COPASI [3] iBioSim [4]. CellDesigner [5] Tellurium[6] Morpheus[7] libRoadRunner
Current version
(stable)
2021.3
(Sep 2021)
4.34
(Aug 2021)
3.0.0
(Sep 2017)
4.4.2
(Jun 2020)
2.2.0
(Dec 2019)
2.2.6
(Feb 2022)
1.4.18
(May 2017)
Capabilities
1. Model creation visual\text-based via tables visual visual text-based via tables via direct API
2. Simulation + + + + + + +
3. Parameter fitting + + - - +/- (3rd party
python libraries)
+ via python/Julia
4. Model analysis + + + - + + +
5. Unique or rare features Parameter identifiability,
Manual parameter fitting
Generic nonlinear optimization Markov Chain analysis
using state-based abstraction
- + MopheusML language for
multicellular and multiscale modeling,
spatial models,
Cellular Potts models
+
6. Database access + - + + +/- (3rd party
python libraries)
- -
7. Jupyter notebooks + + + - + - +
Model formalism
1. ODE + + + + + + +
2. Stochastic Gillespie-type + + + + + + +
3. Algebraic + - + - + + -
4. Discrete + + + + + + +
5. Flux balance + - + - - - -
6. Modular modeling + - + - + + +
7. Mixed formalisms + - + - - + -
8. Agent-based + - + - - + -
9. Rule-based + - - - - + -
10. Population-based + - + - - + -
11. Cellular Potts Models - - - - - + -
Systems Biology Markup Language
1. level and version l3v2 (all tests passed) l3v2 except
algebraic
l3v2 l2v4 l3v2, except
algebraic, delay
l3v2, except
algebraic
l3v2 except
algebraic, delay
3. comp package fully, all tests passed import partially - partially partially partially
4. fbc package + - + - - - -
5. arrays package - - + - - - -
6. layout package - - + - - - -
Other Standards
1. SBGN PD + export - + - - -
2. SBGN-ML + - - + - - -
3. SedML + + + + + - -
4. Combine archive + + + - + - -
5. SBOL - - + - - - -
6. Antimony + - - - + - -
7. Bionetgen + (standalone) - - - - - -
8. BioPAX + - - + - - -
Availability
1. Windows + + + + + + +
2. Linux + + + + + + +
3. MacOS + + + + + + +
4. Web application + + - - via Colab - via Colab
Programming Language Java C++ Java/С Java Python/Julia C++ C/C++/Pyhton/Julia

References

  1. Maggioli, F., Mancini, T., Tronci, E. (2020). SBML2Modelica: integrating biochemical models within open-sThis comparison was made in February 2022. Previous was done in 2019 and is available at separate page Tools Comparison.tandard simulation ecosystems. Bioinformatics, 36(7), 2165-2172. doi:https://doi.org/10.1093/bioinformatics/btz860
  2. Kolpakov, F., Akberdin, I., Kashapov, T., Kiselev, L., Kolmykov, S., Kondrakhin, Y., Kutumova, E., Mandrik, N., Pintus, S., Ryabova, A. and Sharipov, R. (2019). BioUML: an integrated environment for systems biology and collaborative analysis of biomedical data. Nucleic acids research, 47(W1), W225-W233. doi:https://doi.org/10.1093/nar/gkz440
  3. Hoops S., Sahle S., Gauges R., Lee C., Pahle J., Simus N., Singhal M., Xu L., Mendes P. and Kummer U. (2006). COPASI: a COmplex PAthway SImulator. Bioinformatics 22, 3067-74.
  4. Watanabe, L., Nguyen, T., Zhang, M., Zundel, Z., Zhang, Z., Madsen, C., Roehner, N., Myers, C. (2018). iBioSim 3: a tool for model-based genetic circuit design. ACS synthetic biology, 8(7), 1560-1563. doi:https://doi.org/10.1021/acssynbio.8b00078
  5. Funahashi, A., Tanimura, N., Morohashi, M., and Kitano, H., CellDesigner: a process diagram editor for gene-regulatory and biochemical networks, BIOSILICO, 1:159-162, 2003
  6. Choi K., Medley K., König M., Stocking K., Smith L., Gu S., Sauro, H.M. Tellurium: An extensible python-based modeling environment for systems and synthetic biology, Biosystems, Volume 171, 2018, Pages 74-79. doi:https://doi.org/10.1016/j.biosystems.2018.07.006.
  7. J. Starruß, W. de Back, L. Brusch and A. Deutsch. Morpheus: a user-friendly modeling environment for multiscale and multicellular systems biology. Bioinformatics, 30 (9): 1331-1332, 2014.
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