tracyrage / muddy_db

muddy_db - mud volcano database

muddy_db

Description

muddy_db represents a biologically-oriented mud volcano database. It aggregates mud volcano specific terminology and taxonomy, which were mined from open-access articles, available in the S2ORC database, CC BY-NC 2.0, unmodified by (Lo et al. 2020). We used ScispaCy (Neumann et al. 2019) models and ETE3 (Huerta-Cepas, Serra, and Bork 2016) library to check taxonomy-flavored tokens against NCBI Taxonomy database.

Check muddy_db web app: muddy_db

Check our mining pipeline: muddy_mine

Check the published PeerJ article.

Cite this work Remizovschi A, Carpa R. 2021. Biologically-oriented mud volcano database: muddy_db. PeerJ 9:e12463 https://doi.org/10.7717/peerj.12463.

Data

muddy_db includes the following data:

• Bacterial and archaeal taxonomy (phylum, class, order, family, genus)
• Chemistry (inorganic ions, hydrocarbons)
• Geology (geological periods, minerals)
• Mud volcano specific data (microbial consortia, metabolic pathways etc.)
• Methods (amplified genes, analytics)

Install locally

1. Install package

remotes::install_github('TracyRage/muddy_db')

2. Run muddy_db

muddy::run_app()

References

Huerta-Cepas, Jaime, François Serra, and Peer Bork. 2016. “ETE 3: Reconstruction, Analysis, and Visualization of Phylogenomic Data.” Molecular Biology and Evolution 33 (6): 1635–38. https://doi.org/10.1093/molbev/msw046.

Lo, Kyle, Lucy Lu Wang, Mark Neumann, Rodney Kinney, and Daniel Weld. 2020. “S2ORC: The Semantic Scholar Open Research Corpus.” In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 4969–83. Online: Association for Computational Linguistics. https://doi.org/10.18653/v1/2020.acl-main.447.

Neumann, Mark, Daniel King, Iz Beltagy, and Waleed Ammar. 2019. “ScispaCy: Fast and Robust Models for Biomedical Natural Language Processing.” In Proceedings of the 18th BioNLP Workshop and Shared Task, 319–27. Florence, Italy: Association for Computational Linguistics. https://doi.org/10.18653/v1/W19-5034.