JSBML is a community-driven project to create a free, open-source, pure Java library for reading, writing, and manipulating SBML files and data streams. It is an alternative to the mixed Java/native code-based interface provided in libSBML.
JSBML development goals and plans
The JSBML project's aim is to provide an SBML parser and programming library that maps all SBML elements to a flexible and extended type hierarchy. Where possible, JSBML strives to attain 100% API compatibility with the libSBML Java API, to facilitate a switch from one library to the other. Currently, JSBML supports all constructs for SBML up to the latest Level 3 Version 1 Release 1 specification, including an API to add SBML extensions. There are no plans to re-implement some of the more complex functions of libSBML such as consistency-checking and SBML validation; instead, these will be accessed via web services.
Article citations are crucial to our academic careers. If you use JSBML, we ask that you please cite one of the following papers:
Nicolas Rodriguez, Alex Thomas, Leandro Watanabe, Ibrahim Y. Vazirabad, Victor Kofia, Harold F. Gómez, Florian Mittag, Jakob Matthes, Jan Rudolph, Finja Wrzodek, Eugen Netz, Alexander Diamantikos, Johannes Eichner, Roland Keller, Clemens Wrzodek, Sebastian Fröhlich, Nathan E. Lewis, Chris J. Myers, Nicolas Le Novère, Bernhard Ø. Palsson, Michael Hucka, and Andreas Dräger. JSBML 1.0: providing a smorgasbord of options to encode systems biology models. Bioinformatics, June 2015. (Freely available directly from Bioinformatics.)
Dräger A, Rodriguez N, Dumousseau M, Dörr A, Wrzodek C, Le Novère N, Zell A, and Hucka M. JSBML: a flexible Java library for working with SBML. Bioinformatics (2011), 27(15):2167–2168. (Freely available directly from Bioinformatics.)
There is a mailing list and web forum, jsbml-development, devoted to discussions about JSBML. There's also a JSBML group on LinkedIn. If you're on LinkedIn and interested in JSBML, feel free to join the group!
JSBML is the result of hard work by many people, including several (Ph.D.) students. We thank the following contributors especially (in alphabetical order):
Meike Aichele1, Alexander Diamantikos1, Alexander Dörr1, Andreas Dräger1,2, Marine Dumousseau3, Johannes Eichner1, Sebastian Fröhlich4, Harold F. Gómez5 Michael Hucka6, Roland Keller1, Victor Kofia7, Jakob Matthes1, Florian Mittag1,3, Sarah Rachel Müller vom Hagen1, Sebastian Nagel1, Eugen Netz1, Alexander Peltzer1, Nicolas Rodriguez3,8, Jan Rudolph1, Simon Schäfer1, Alex Thomas2, Ibrahim Y. Vazirabad9, Leandro Watanabe10, Clemens Wrzodek1, Finja Wrzodek1,3
JSBML principal investigators:
Nicolas Le Novère3,7
Chris J. Myers10
Nathan E. Lewis2
Bernhard Ø. Palsson2
1Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, Tübingen, Germany,
2University of California, San Diego, La Jolla, CA, USA
3European Bioinformatics Institute (EBI), Hinxton, UK,
4Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany
5Boston University, Boston, MA, USA
6The California Institute of Technology, Pasadena, CA, USA
7The University of Toronto, Toronto, ON, Canada
8Babraham Institute, Babraham Research Campus, Cambridge, UK
9Marquette University, Milwaukee, WI, USA
10The University of Utah, Salt Lake City, UT, USA
The development of JSBML is funded in part by a grant from the National Institute of General Medical Sciences (NIGMS, USA, award number GM070923), as well as by funds from the Babraham Institute (UK), a Marie-Curie International Outgoing Fellowship (IOF) within the European Commision's 7th Framework Programme for Research and Technological Development (project AMBiCon grant number 332020). Google supports this work as part of the Google Summer of Code 2014 initiative.
Further support comes from the Federal Ministry of Education and Research (BMBF, Germany) in the Virtual Liver Network and the MedSys project Spher4Sys as well as the University of Tübingen (Germany).