Software:SBSCL

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SBSCL
Original author(s)Andreas Dräger, Roland Keller, Alexander Dörr
Developer(s)Community contributors
Initial releaseAugust 12, 2011; 14 years ago (2011-08-12)
Stable release
2.1 / April 21, 2021; 4 years ago (2021-04-21)
Written inJava™
Operating systemLinux, macOS and Microsoft Windows
LicenseLGPL
Websitegithub.com/draeger-lab/SBSCL

The Systems Biology Simulation Core Library (SBSCL)Cite error: Closing </ref> missing for <ref> tag[1] , enables platform-independent model simulation across any environment supporting the Java Virtual Machine. It includes a comprehensive suite of numerical methods for solving ordinary differential equations and other dynamic behaviors described in biological models.

SBSCL is designed as a reusable software library and does not come with a GUI or a CLI by default. Instead, it is intended to be embedded into larger software projects where custom user interfaces can be developed as needed. Researchers can also integrate SBSCL directly into their Java projects via its Apache Maven or Gradle dependency to programmatically simulate SBML models.

Capabilities

SBSCL offers a wide range of features for simulating and analyzing computational models in systems biology.

1. Numerical simulation in an ordinary differential equation framework

  • LSODA-Integrator (Livermore Solver for Ordinary Differential Equation Automatic) for the simulation of models containing general ODEs
  • Rosenbrock solver for the integration of stiff differential equation systems
  • Several solvers from the Apache Commons Math[2] Library are included.
  • Clear separation of SBML interpretation and integration routines
  • Fast SBML interpretation by using a transformed syntax graph
  • Full support of SBML events, algebraic rules, and fast reactions
  • Support of all models from the SBML Test Suite for all levels and versions
  • Compatible with Flux Balance Constraints (fbc) and Hierarchical Model Composition (comp) extensions.

2. Stochastic simulation framework

  • Supports different solvers from the FERN library
  • The Gillespie Algorithm is used currently to solve the SBML models.
  • Support of models from the Stochastic Test Suite for all levels and versions

3. Linear optimization framework

  • Incorporation of external implementations of the simplex algorithm in libraries, such as Gurobi, CPLEX, and many more, supports simulating models via linear optimization.
  • At the moment, the implementation comprises flux balance analysis.

4. Support for SED-ML

  • Fully interprets and simulates models described in the Simulation Experiment Description Markup Language (SED-ML).

5. Data Analysis Functions

  • Several quality functions can compute the distance from simulated data to given data and provide a basis for model calibration.

6. Application Programming Interface Support

  • Offers a well-defined API, enabling integration into other software projects or direct use in Java applications via Apache Maven or Gradle.

Supported Packages

  • Systems Biology Markup Language (L1V1 - L3V2)
  • SBML models with fbc V1 and V2
  • SBML models with comp extensions
  • Simulation Experiment Description Markup Language (L1V3)
  • COMBINE archive and OMEX format
  • All models from the SBML Test Suite and the BiGG models database
  • All models from the Stochastic Test Suite

Application

  • SBSCL has been part of the systems biology community for several years and its adoption has also increased widely with time, primarily in research environments for the simulation of SBML models.
  • It also hosts different SBML-related software like SBMLsimulator[3] and CellDesigner[4].
  • It has also been used to model zinc transportation in Bacillus spp[5]. and to conduct research on engineering the non-oxidative glycolytic pathway in Streptomyces toxytricini[6]

See also

References

  1. ↑ Rodriguez, N.; Thomas, A.; Watanabe, L.; Vazirabad, I. Y.; Kofia, V.; Gómez, H. F.; Mittag, F.; Matthes, J. et al. (2022). "JSBML 1.0: providing a smorgasbord of options to encode systems biology models". Bioinformatics 31 (20): 3383–3386. doi:10.1093/bioinformatics/btv341. PMID 26079347. PMC 4595895. http://bioinformatics.oxfordjournals.org/content/early/2015/06/30/bioinformatics.btv341.full.pdf. 
  2. ↑ "The Apache Commons Mathematics Library". https://commons.apache.org/proper/commons-math/. 
  3. ↑ Dörr, Alexander; Keller, Roland; Zell, Andreas; Dräger, Andreas (18 December 2014). "SBMLSimulator: A Java Tool for Model Simulation and Parameter Estimation in Systems Biology". Computation 2 (4): 246–257. doi:10.3390/computation2040246. PMID 32211200. 
  4. ↑ Funahashi, Akira; Morohashi, Mineo; Kitano, Hiroaki; Tanimura, Naoki (November 2003). "CellDesigner: a process diagram editor for gene-regulatory and biochemical networks". Biosilico 1 (5): 159–162. doi:10.1016/S1478-5382(03)02370-9. 
  5. ↑ Bhatt, Kalpana; Maheshwari, Dinesh Kumar (22 January 2022). "Insights into zinc-sensing metalloregulator 'Zur' deciphering mechanism of zinc transportation in Bacillus spp. by modeling, simulation and molecular docking". Journal of Biomolecular Structure and Dynamics 40 (2): 764–779. doi:10.1080/07391102.2020.1818625. PMID 32924811. 
  6. ↑ Jatain, Indu; Yadav, Karuna; Nitharwal, Ram Gopal; Arora, Devender; Dubey, Kashyap Kumar (September 2022). "A system biology approach for engineering non-oxidative glycolysis pathway in Streptomyces toxytricini for high lipstatin biosynthesis". Bioresource Technology Reports 19. doi:10.1016/j.biteb.2022.101188. Bibcode: 2022BiTeR..1901188J. 



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