High-dimensional supervised classification in a context of non-independence of observations to identify the determining SNPs in a phenotype.
- 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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Cite this work
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
Source records
- pubmed · retrieved 2026-09-26T16:24:02.334Z