Difference between revisions of "Tools Comparison 2022"

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Here we collect information about similar software and their features in comparison with BioUML.<br.\>
+
Here we collect information about similar software and their features in comparison with BioUML.
This comparison was made in February 2022. Previous was done in 2019 and is available at separate page [[Tools Comparison]].
+
 
<br><br>
+
 
== Comparisons made by third parties ==
 
== Comparisons made by third parties ==
 
<ul>
 
<ul>
Line 7: Line 6:
 
<li>Extensive comparison of different simulators according to their speed and percentage of passed SBML tests was performed by Maggioli et al.<ref>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}}</ref>
 
<li>Extensive comparison of different simulators according to their speed and percentage of passed SBML tests was performed by Maggioli et al.<ref>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}}</ref>
 
</ul>
 
</ul>
<br><br>
 
  
== Modeling tools comparison 2022==
+
== Modeling tools comparison ==
 +
 
 +
This comparison was made in February 2022. Previous was done in 2019 and is available at separate page [[Tools Comparison]].<br>
  
 
{| class="wikitable"
 
{| class="wikitable"
 
|+
 
|+
 
|
 
|
|BioUML
+
|[http://wiki.biouml.org/ BioUML] <ref>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}}
|COPASI
+
</ref>
|iBioSim
+
|[http://copasi.org/ COPASI] <ref>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.</ref>
|CellDesigner
+
|[https://async.ece.utah.edu/tools/ibiosim/ iBioSim] <ref>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}}</ref>.
|Tellurium
+
 
|Morpheus
+
|[https://www.celldesigner.org/ CellDesigner] <ref>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</ref>
|libRoadRunner
+
|[http://libroadrunner.org/ Tellurium]<ref>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}}.</ref>
 +
|[https://morpheus.gitlab.io/ Morpheus]<ref>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.</ref>
 +
|[http://libroadrunner.org/ libRoadRunner]
 
|-
 
|-
|'''Link'''
+
| Current version<br>(stable)
| http://wiki.biouml.org/
+
| 2021.3<br> (Sep 2021)
| http://copasi.org/
+
| 4.34<br> (Aug 2021)
| https://async.ece.utah.edu/tools/ibiosim/
+
| 3.0.0<br> (Sep 2017)
| https://www.celldesigner.org/
+
| 4.4.2<br> (Jun 2020)
| https://tellurium.analogmachine.org/
+
| 2.2.0<br> (Dec 2019)
| https://morpheus.gitlab.io/
+
| 2.2.6<br> (Feb 2022)
| http://libroadrunner.org/
+
| 1.4.18<br> (May 2017)
 
|-
 
|-
|'''Capabilities'''
+
!colspan="9"| <center>'''Capabilities'''</center>
|
+
|
+
|
+
|
+
|
+
|
+
|
+
 
|-
 
|-
 
|1. Model creation
 
|1. Model creation
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| text-based
 
| text-based
 
| via tables
 
| via tables
|
+
| via direct API
 
|-
 
|-
 
|2. Simulation
 
|2. Simulation
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| +
 
| +
 
| +
 
| +
| via ext.tools
+
| +
 
| +
 
| +
 
| +
 
| +
Line 63: Line 59:
 
| -  
 
| -  
 
| -
 
| -
| -
+
| +/- (3rd party<br>python libraries)
| -
+
| +
|
+
| via python/Julia
 
|-
 
|-
 
|4. Model analysis
 
|4. Model analysis
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| +
 
| +
 
| +
 
| +
|
+
| +
 
|-
 
|-
|5. Database access
+
|5. Unique or rare features
 +
| Parameter identifiability,<br>Manual parameter fitting
 +
| Generic nonlinear optimization
 +
| Markov Chain analysis<br> using state-based abstraction
 +
| Provides a special notation<br>for biochemical reaction networks<br> (i.e. CellDesigner notation)
 +
|
 +
| MopheusML language for<br> multicellular and multiscale modeling,<br>spatial models,<br>Cellular Potts models
 +
|
 +
|-
 +
|6. Database access
 
| +
 
| +
 
| -
 
| -
 
| +
 
| +
 
| +
 
| +
 +
| +/- (3rd party<br>python libraries)
 
| -
 
| -
 
| -
 
| -
|
 
 
|-
 
|-
|6. Jupyter notebooks
+
|7. Jupyter notebooks
 
| +
 
| +
| -
 
 
| +
 
| +
 
| +
 
| +
 
| -
 
| -
 +
| +
 
| -
 
| -
|
+
| +
 
|-
 
|-
|'''Model formalism'''
+
!colspan="9"|<center>'''Model formalism'''</center>
|
+
|
+
|
+
|
+
|
+
|
+
|
+
 
|-
 
|-
 
|1. ODE
 
|1. ODE
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| +
 
| +
 
| +
 
| +
| -
+
| +
 
| +
 
| +
 
| +
 
| +
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| +
 
| +
 
| +
 
| +
|  
+
| -
 
|-
 
|-
 
|4. Discrete
 
|4. Discrete
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| +
 
| +
 
| +
 
| +
|
+
| +
 
|-
 
|-
 
|5. Flux balance
 
|5. Flux balance
|  
+
| +
|  
+
| -
|  
+
| +
|
+
| -
|  
+
| -
|  
+
| -
|
+
| -
 
|-
 
|-
 
|6. Modular modeling
 
|6. Modular modeling
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| +
 
| +
 
| +
 
| +
|
+
| +
 
|-
 
|-
 
|7. Mixed formalisms
 
|7. Mixed formalisms
 
| +
 
| +
 
| -
 
| -
 +
| +
 
| -
 
| -
 
| -
 
| -
 +
| +
 
| -
 
| -
| +
 
|
 
 
|-
 
|-
 
|8. Agent-based
 
|8. Agent-based
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| -
 
| -
 
| -
 
| -
 +
| +
 
| -
 
| -
|
 
 
|-
 
|-
 
|9. Rule-based
 
|9. Rule-based
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| -
 
| -
 
| -
 
| -
 +
| +
 
| -
 
| -
|
 
 
|-
 
|-
 
|10. Population-based
 
|10. Population-based
 
| +
 
| +
 
| -
 
| -
 +
| +
 
| -
 
| -
 
| -
 
| -
 +
| +
 +
| -
 +
|-
 +
|11. Cellular Potts Models
 
| -
 
| -
 
| -
 
| -
|
+
| -
 +
| -
 +
| -
 +
| +
 +
| -
 
|-
 
|-
|'''Standards'''
+
!colspan="9"|'''Systems Biology Markup Language'''
|
+
|
+
|
+
|
+
|
+
|
+
|
+
 
|-
 
|-
|1. SBML
+
|1. level and version
| l3v2, all tests passed
+
| l3v2 (all tests passed)
| l3v1 except algebraic
+
| l3v2 except<br>algebraic
| l3v1
+
| l3v2
| l3v1
+
| l2v4
| l3v1
+
| l3v2, except<br>algebraic, delay
| l3v1, partially
+
| l3v2, except<br>algebraic
|
+
| l3v2 except<br>algebraic, delay
 
|-
 
|-
|2. SBML comp
+
|2. comp
| fully, all tests passed
+
| fully (all tests passed)
 +
| import
 +
| fully (all tests passed)
 
| -
 
| -
 
| partially
 
| partially
| -
 
 
| partially
 
| partially
 
| partially
 
| partially
|
 
 
|-
 
|-
|3. SBML fbc
+
|3. fbc
| fully, all tests passed
+
| +
|  
+
| -
|  
+
| +
|  
+
| -
|  
+
| -
|  
+
| -
|
+
| -
 
|-
 
|-
|4. SBGN PD
+
|4. arrays
 +
| -
 +
| -
 
| +
 
| +
| export
+
| -
 +
| -
 +
| -
 +
| -
 +
|-
 +
|5. distrib
 +
| -
 
| -
 
| -
 
| +
 
| +
 
| -
 
| -
 
| -
 
| -
|
+
| -
 +
| -
 
|-
 
|-
|5. SBGN-ML
+
|6. layout
|  
+
| -
|  
+
| -
|  
+
| +
|  
+
| -
|  
+
| -
|  
+
| -
|
+
| -
 
|-
 
|-
|6. SedML
+
!colspan="9"|'''Other Standards'''
 +
|-
 +
|1. SBGN PD
 
| +
 
| +
 +
| export
 +
| -
 
| +
 
| +
 
| -
 
| -
 
| -
 
| -
 +
| -
 +
|-
 +
|2. SBGN-ML
 
| +
 
| +
 
| -
 
| -
|
+
| -
 +
| +
 +
| -
 +
| -
 +
| -
 
|-
 
|-
|7. Combine archive
+
|3. SedML
|  
+
| +
|  
+
| +
|  
+
| +
|  
+
| +
|  
+
| +
|  
+
| -
|
+
| -
 +
|-
 +
|4. Combine archive
 +
| +
 +
| +
 +
| +
 +
| -
 +
| +
 +
| -
 +
| -
 
|-
 
|-
|8. SBOL
+
|5. SBOL
 
| -
 
| -
 
| -
 
| -
 
| +
 
| +
 
| -
 
| -
 +
| +/- (3rd party<br>python libraries)
 
| -
 
| -
 
| -
 
| -
|
 
 
|-
 
|-
|9. Antimony
+
|6. Antimony
| + (in standalone)
+
| +
 
| -
 
| -
 
| -
 
| -
Line 281: Line 310:
 
| +
 
| +
 
| -
 
| -
|
+
| -
 
|-
 
|-
|10. Bionetgen
+
|7. Bionetgen
| + (in standalone)
+
| + (standalone)
 +
| -
 
| -
 
| -
 
| -
 
| -
Line 290: Line 320:
 
| -
 
| -
 
| -
 
| -
|
 
 
|-
 
|-
|11. BioPAX
+
|8. BioPAX
 
| +
 
| +
 
| -
 
| -
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| -
 
| -
 
| -
 
| -
|
+
| -
 
|-
 
|-
|'''Availability'''
+
!colspan="9"|'''Availability'''
|
+
|
+
|
+
|
+
|
+
|
+
|
+
 
|-
 
|-
 
|1. Windows
 
|1. Windows
Line 317: Line 339:
 
| +
 
| +
 
| +
 
| +
|
+
| +
 
|-
 
|-
 
|2. Linux
 
|2. Linux
Line 326: Line 348:
 
| +
 
| +
 
| +
 
| +
|
+
| +
 
|-
 
|-
 
|3. MacOS
 
|3. MacOS
Line 335: Line 357:
 
| +
 
| +
 
| +
 
| +
|
+
| +
 
|-
 
|-
 
|4. Web application
 
|4. Web application
 
| +
 
| +
 +
| [http://shiny.copasi.org +]
 
| -
 
| -
 
| -
 
| -
 +
| via Colab
 
| -
 
| -
| -
+
| via Colab
| -
+
|
+
 
|-
 
|-
 
|'''Programming Language'''
 
|'''Programming Language'''
 
| Java
 
| Java
 
| C++
 
| C++
 +
| Java/С
 
| Java
 
| Java
| Java
+
| Python/Julia
| Python
+
 
| C++
 
| C++
|
+
| C/C++/Pyhton/Julia
 
|}
 
|}
  

Latest revision as of 13:50, 28 March 2022

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

[edit] 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]

[edit] 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
Provides a special notation
for biochemical reaction networks
(i.e. CellDesigner notation)
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
2. comp fully (all tests passed) import fully (all tests passed) - partially partially partially
3. fbc + - + - - - -
4. arrays - - + - - - -
5. distrib - - + - - - -
6. layout - - + - - - -
Other Standards
1. SBGN PD + export - + - - -
2. SBGN-ML + - - + - - -
3. SedML + + + + + - -
4. Combine archive + + + - + - -
5. SBOL - - + - +/- (3rd party
python libraries)
- -
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

[edit] 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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