PerCon SFA Snekmer KBase Narrative App
Creators
Description
The Snekmer KBase App is an extension toolkit that allows for running supervised modeling and unsupervised clustering from protein family scores and/or searching unknown sequences for protein families using the Snekmer workflow within the KBase narrative user interface.
- KBase Narrative Information: Snekmer Catalog Status (Running v2.2.4 of the Catalog Server)
- Narrative App Methods:
Federal Acknowledgements
This research was supported in part by the U.S. Department of Energy (DOE), Office of Biological and Environmental Research (BER), as part of the Genomic Science Program (GSP) as a contribution of the Pacific Northwest National Laboratory (PNNL) Secure Biosystems Design Science Focus Area: Persistence Control of Engineered Functions in Complex Soil Microbiomes (PerCon SFA). Pacific Northwest National Laboratory (PNNL) is a multiprogram national laboratory managed by the Battelle Memorial Institute Battelle Memorial Institute, operating under the U.S. Department of Energy, Contract DE-AC05-76RL01830.
Notes (En)
Files
Snekmer-KBase-App-main.zip
Files
(78.6 MB)
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md5:ddcbfa62d5f6c28bce463471a0771106
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Additional details
Related works
- Is documented by
- Other: https://narrative.kbase.us/#catalog/modules/Snekmer (URL)
- Requires
- Software: https://github.com/kbase/kb_sdk (URL)
Software
- Repository URL
- https://github.com/PerConSFA/Snekmer-KBase-App
- Programming language
- Python
References
- McDermott, J. E., Chang, C. H., Jerger, A., Nelson, W. B., & Jacobson, J. R. (2023). Snekmer: A scalable pipeline for protein sequence fingerprinting using amino acid recoding (AAR) (v1.0.4). Zenodo. https://doi.org/10.5281/zenodo.7662597
- Christine H Chang, William C Nelson, Abby Jerger, Aaron T Wright, Robert G Egbert, Jason E McDermott, Snekmer: a scalable pipeline for protein sequence fingerprinting based on amino acid recoding, Bioinformatics Advances, Volume 3, Issue 1, 2023, vbad005, https://doi.org/10.1093/bioadv/vbad005
Subjects
- software module
- http://semanticscience.org/resource/SIO_000099
- Python script
- http://edamontology.org/format_3996
- machine learning
- https://w3id.org/aio/Machine_Learning
- amino acid protein sequence data
- http://www.ebi.ac.uk/swo/data/SWO_3000067
- sequence analysis
- http://edamontology.org/topic_0080
- unsupervised clustering
- https://w3id.org/aio/Unsupervised_Clustering
- supervised learning
- https://w3id.org/aio/Supervised_Learning