Determining Optimal Features for Predicting Type IV Secretion System Effector Proteins for Coxiella burnetii
Author:
Affiliation:
1. Washington State University, Pullman, WA, USA
Funder
This research was supported by National Institutes of Health grant R01AI042792 and by the Carl M. Hansen Foundation.
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3107411.3107416
Reference21 articles.
1. Bacterial Type IV secretion systems: versatile virulence machines
2. The Coxiella burnetii Cryptic Plasmid Is Enriched in Genes Encoding Type IV Secretion System Substrates
3. Searching algorithm for type IV secretion system effectors 1.0: a tool for predicting type IV effectors and exploring their genomic context
4. Accurate prediction of bacterial type IV secreted effectors using amino acid composition and PSSM profiles
5. SecretP: Identifying bacterial secreted proteins by fusing new features into Chou’s pseudo-amino acid composition
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1. T4SE-XGB: Interpretable Sequence-Based Prediction of Type IV Secreted Effectors Using eXtreme Gradient Boosting Algorithm;Frontiers in Microbiology;2020-09-24
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