Examining the predictive accuracy of the novel 3D N-linear algebraic molecular codifications on benchmark datasets.
- DOI
- 10.1186/s13321-016-0122-x
- Published
- 2016
- Container
- Journal of cheminformatics
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1186/s13321-016-0122-x,
title = {Examining the predictive accuracy of the novel 3D N-linear algebraic molecular codifications on benchmark datasets.},
author = {García-Jacas CR and Contreras-Torres E and Marrero-Ponce Y and Pupo-Meriño M and Barigye SJ and Cabrera-Leyva L},
year = {2016},
journal = {Journal of cheminformatics},
doi = {10.1186/s13321-016-0122-x},
url = {https://doi.org/10.1186/s13321-016-0122-x}
}RIS
TY - JOUR TI - Examining the predictive accuracy of the novel 3D N-linear algebraic molecular codifications on benchmark datasets. AU - García-Jacas CR AU - Contreras-Torres E AU - Marrero-Ponce Y AU - Pupo-Meriño M AU - Barigye SJ AU - Cabrera-Leyva L PY - 2016 JO - Journal of cheminformatics DO - 10.1186/s13321-016-0122-x UR - https://doi.org/10.1186/s13321-016-0122-x ER -
APA
CR, G., E, C., Y, M., M, P., SJ, B., & L, C. (2016). Examining the predictive accuracy of the novel 3D N-linear algebraic molecular codifications on benchmark datasets.. Journal of cheminformatics. https://doi.org/10.1186/s13321-016-0122-x
Source records
- pubmed · retrieved 2026-09-26T19:59:36.925Z