An optimal set of features for predicting type IV secretion system effector proteins for a subset of species based on a multi-level feature selection approach.
- DOI
- 10.1371/journal.pone.0197041
- Published
- 2018
- Container
- PloS one
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1371/journal.pone.0197041,
title = {An optimal set of features for predicting type IV secretion system effector proteins for a subset of species based on a multi-level feature selection approach.},
author = {Esna Ashari Z and Dasgupta N and Brayton KA and Broschat SL},
year = {2018},
journal = {PloS one},
doi = {10.1371/journal.pone.0197041},
url = {https://doi.org/10.1371/journal.pone.0197041}
}RIS
TY - JOUR TI - An optimal set of features for predicting type IV secretion system effector proteins for a subset of species based on a multi-level feature selection approach. AU - Esna Ashari Z AU - Dasgupta N AU - Brayton KA AU - Broschat SL PY - 2018 JO - PloS one DO - 10.1371/journal.pone.0197041 UR - https://doi.org/10.1371/journal.pone.0197041 ER -
APA
Z, E. A., N, D., KA, B., & SL, B. (2018). An optimal set of features for predicting type IV secretion system effector proteins for a subset of species based on a multi-level feature selection approach.. PloS one. https://doi.org/10.1371/journal.pone.0197041
Source records
- pubmed · retrieved 2026-09-25T17:50:53.095Z