References
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If you find PyBEL useful for your work, please consider citing [1]_:

.. [1] Hoyt, C. T., *et al.* (2017). `PyBEL: a Computational Framework for Biological Expression Language
       <https://doi.org/10.1093/bioinformatics/btx660>`_. Bioinformatics, 34(December), 1–2.

Related Publications
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We have used PyBEL in several other projects and publications. Below is a sample:

- Domingo-Fernández, D., Mubeen, S., Marin-Llao, J., Hoyt, C. T., & Hofmann-Apitius, M. (2018). PathMe: Merging and
  exploring mechanistic pathway knowledge. bioRxiv, 451625.
- Domingo-Fernández, D., Hoyt, C. T., Alvarez, C. B., Marin-Llao, J., Hofmann-Apitius, M. (2018). ComPath: an ecosystem
  for exploring, analyzing, and curating mappings across pathway databases. Npj Systems Biology and Applications,
  5(1), 3. https://doi.org/10.1038/s41540-018-0078-8
- Hoyt, C. T., et al. (2018). A systematic approach for identifying shared mechanisms in epilepsy and its
  comorbidities. Database, 2018(1). https://doi.org/10.1093/database/bay050
- Hoyt, C. T., et al. (2019). Re-curation and Rational Enrichment of Knowledge Graphs in Biological Expression
  Language. BioRxiv, 536409. https://doi.org/10.1101/536409
- Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and
  analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.
  https://doi.org/10.1093/database/bay126
- Ali, M., et al. (2019). BioKEEN: A library for learning and evaluating biological knowledge graph embeddings.
  Bioinformatics, btz117. https://doi.org/10.1093/bioinformatics/btz117

Software using PyBEL
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- https://github.com/cthoyt/bel-repository
- https://github.com/bio2bel
- https://github.com/sorgerlab/indra
- https://github.com/smartDataAnalytics/biokeen

BEL Content
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- https://github.com/neurommsig/neurommsig-knowledge
- https://github.com/pharmacome/knowledge
