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.

Esna Ashari Z, Dasgupta N, Brayton KA, Broschat SL

Open source

DOI
10.1371/journal.pone.0197041
Published
2018
Container
PloS one
Publisher
Not recorded
Open access
yes

Credibility signals

limited evidence Score 45/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

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