High-dimensional supervised classification in a context of non-independence of observations to identify the determining SNPs in a phenotype.

Gaye A, Diongue AK, Komen LN, Diallo A, Sylla SN, Diarra M, Talla C, Loucoubar C

Open source

DOI
10.1016/j.idm.2023.09.002
Published
2023 Dec
Container
Infectious Disease Modelling
Publisher
Not recorded
Open access
yes

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BibTeX

@article{allodium:10.1016/j.idm.2023.09.002,
  title = {High-dimensional supervised classification in a context of non-independence of observations to identify the determining SNPs in a phenotype.},
  author = {Gaye A and Diongue AK and Komen LN and Diallo A and Sylla SN and Diarra M and Talla C and Loucoubar C},
  year = {2023},
  journal = {Infectious Disease Modelling},
  doi = {10.1016/j.idm.2023.09.002},
  url = {https://doi.org/10.1016/j.idm.2023.09.002}
}

RIS

TY  - JOUR
TI  - High-dimensional supervised classification in a context of non-independence of observations to identify the determining SNPs in a phenotype.
AU  - Gaye A
AU  - Diongue AK
AU  - Komen LN
AU  - Diallo A
AU  - Sylla SN
AU  - Diarra M
AU  - Talla C
AU  - Loucoubar C
PY  - 2023
JO  - Infectious Disease Modelling
DO  - 10.1016/j.idm.2023.09.002
UR  - https://doi.org/10.1016/j.idm.2023.09.002
ER  - 

APA

A, G., AK, D., LN, K., A, D., SN, S., M, D., C, T., & C, L. (2023). High-dimensional supervised classification in a context of non-independence of observations to identify the determining SNPs in a phenotype.. Infectious Disease Modelling. https://doi.org/10.1016/j.idm.2023.09.002

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