SemGen

SemGen is an experimental software tool for automating the modular composition and decomposition of biosimulation models.

SemGen facilitates the construction of complex, integrated models, and the swift extraction of reusable sub-models from larger ones. SemGen relies on the semantically-rich SemSim model description format to help automate these modeling tasks.

With SemGen, users can

• Visualize models using D3 force-directed networks

• Create SemSim versions of existing models and annotate them with rich semantic data

• Automatically decompose models into interoperable sub-models

• Semi-automatically merge models into more complex systems

• Encode models in executable simulation formats

Click here for more background on SemGen and a detailed software guide

This software is experimental and we encourage feedback, bug reports, etc. from all users. We intend to improve SemGen through user-based development, so feel free to contact us directly if you are interested in using and improving SemGen.

Dr. Maxwell Neal originally developed the SemGen software as part of his dissertation research. Currently, Dr. Neal leads a team of developers to further augment, test and evaluate SemGen under an R01 grant from the National Library of Medicine (PIs: John Gennari and Brian Carlson) that aims to accelerate model-driven research. Contributors to SemGen development include Christopher Thompson, Graham Kim and Ryan James.

How to cite SemGen:

Neal ML, Thompson CT, Kim KG, James RC, Cook DL, Carlson BE, Gennari JH. SemGen: a tool for semantics-based annotation and composition of biosimulation models. Bioinformatics. 2019. 35(9):1600–1602.

SemGen has been developed with support from the American Heart Association, the European Commission, and the United States National Institutes of Health.