DNA-based prediction of eye color in Latin American population applying Machine Learning models

Cristian A. Martínez; Diana M. Hohl; María de los A. Gutiérrez; Sagnik Palmal; Pierre Faux; Kaustubh Adhikari; Rolando Gonzalez-Jose; Maria C. Bortolini; Victor Acuña-Alonzo; Carla Gallo; Andres Ruiz Linares; Francisco Rothhammer; Cecilia I. Catanesi; Ricardo J. Barrientos

doi:10.1016/j.compbiomed.2025.110404

DNA-based prediction of eye color in Latin American population applying Machine Learning models

Cristian A. Martínez
, Diana M. Hohl
, María de los A. Gutiérrez
, Sagnik Palmal
, Pierre Faux
, Kaustubh Adhikari
, Rolando Gonzalez-Jose
, Maria C. Bortolini
, Victor Acuña-Alonzo
, Carla Gallo
, Andres Ruiz Linares
, Francisco Rothhammer
, Cecilia I. Catanesi
, Ricardo J. Barrientos

Facultad de Ciencias e Ingeniería

Catholic University of the Maule
CONICET
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires CICPBA
Université de Lille
Université de Toulouse
The Open University
CENPAT-CONICET
Universidade Federal do Rio Grande do Sul
National Institute of Anthropology and History
Fudan University
ADES
University College London
Instituto de Alta Investigación Universidad de Tarapacá
Museo de La Plata

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

3 Citas (Scopus)

Resumen

Reduction in the costs of DNA sequencing and genotyping allows for the increased availability of databases which can be useful for analyzing the relationship between the human genetic code and visible characteristics, diseases, and behaviors, among others. The aim of this study is to improve the prediction of eye color from genotype by means of several Machine Learning models, using a dataset of 308 volunteers from Buenos Aires, Argentina. The results achieved are competitive and demonstrate the usefulness of artificial intelligence (AI) in the fields of genetics and its application in areas such as health, biometrics and forensics.

Idioma original	Inglés
Número de artículo	110404
Publicación	Computers in Biology and Medicine
Volumen	194
DOI	https://doi.org/10.1016/j.compbiomed.2025.110404
Estado	Publicada - ago. 2025

Acceder al documento

10.1016/j.compbiomed.2025.110404

Otros archivos y enlaces

Enlace a la publicación en Scopus

Citar esto

Martínez, C. A., Hohl, D. M., Gutiérrez, M. D. L. A., Palmal, S., Faux, P., Adhikari, K., Gonzalez-Jose, R., Bortolini, M. C., Acuña-Alonzo, V., Gallo, C., Linares, A. R., Rothhammer, F., Catanesi, C. I., & Barrientos, R. J. (2025). DNA-based prediction of eye color in Latin American population applying Machine Learning models. Computers in Biology and Medicine, 194, Artículo 110404. https://doi.org/10.1016/j.compbiomed.2025.110404

@article{4b6e3e6371a14831b1f324005ca1c48d,

title = "DNA-based prediction of eye color in Latin American population applying Machine Learning models",

abstract = "Reduction in the costs of DNA sequencing and genotyping allows for the increased availability of databases which can be useful for analyzing the relationship between the human genetic code and visible characteristics, diseases, and behaviors, among others. The aim of this study is to improve the prediction of eye color from genotype by means of several Machine Learning models, using a dataset of 308 volunteers from Buenos Aires, Argentina. The results achieved are competitive and demonstrate the usefulness of artificial intelligence (AI) in the fields of genetics and its application in areas such as health, biometrics and forensics.",

keywords = "DNA phenotyping, Eye color prediction, Forensic DNA, Machine Learning",

author = "Mart{\'i}nez, \{Cristian A.\} and Hohl, \{Diana M.\} and Guti{\'e}rrez, \{Mar{\'i}a de los A.\} and Sagnik Palmal and Pierre Faux and Kaustubh Adhikari and Rolando Gonzalez-Jose and Bortolini, \{Maria C.\} and Victor Acu{\~n}a-Alonzo and Carla Gallo and Linares, \{Andres Ruiz\} and Francisco Rothhammer and Catanesi, \{Cecilia I.\} and Barrientos, \{Ricardo J.\}",

note = "Publisher Copyright: {\textcopyright} 2025 Elsevier Ltd",

year = "2025",

month = aug,

doi = "10.1016/j.compbiomed.2025.110404",

language = "Ingl{\'e}s",

volume = "194",

journal = "Computers in Biology and Medicine",

issn = "0010-4825",

}

Martínez, CA, Hohl, DM, Gutiérrez, MDLA, Palmal, S, Faux, P, Adhikari, K, Gonzalez-Jose, R, Bortolini, MC, Acuña-Alonzo, V, Gallo, C, Linares, AR, Rothhammer, F, Catanesi, CI & Barrientos, RJ 2025, 'DNA-based prediction of eye color in Latin American population applying Machine Learning models', Computers in Biology and Medicine, vol. 194, 110404. https://doi.org/10.1016/j.compbiomed.2025.110404

TY - JOUR

T1 - DNA-based prediction of eye color in Latin American population applying Machine Learning models

AU - Martínez, Cristian A.

AU - Hohl, Diana M.

AU - Gutiérrez, María de los A.

AU - Palmal, Sagnik

AU - Faux, Pierre

AU - Adhikari, Kaustubh

AU - Gonzalez-Jose, Rolando

AU - Bortolini, Maria C.

AU - Acuña-Alonzo, Victor

AU - Gallo, Carla

AU - Linares, Andres Ruiz

AU - Rothhammer, Francisco

AU - Catanesi, Cecilia I.

AU - Barrientos, Ricardo J.

PY - 2025/8

Y1 - 2025/8

N2 - Reduction in the costs of DNA sequencing and genotyping allows for the increased availability of databases which can be useful for analyzing the relationship between the human genetic code and visible characteristics, diseases, and behaviors, among others. The aim of this study is to improve the prediction of eye color from genotype by means of several Machine Learning models, using a dataset of 308 volunteers from Buenos Aires, Argentina. The results achieved are competitive and demonstrate the usefulness of artificial intelligence (AI) in the fields of genetics and its application in areas such as health, biometrics and forensics.

AB - Reduction in the costs of DNA sequencing and genotyping allows for the increased availability of databases which can be useful for analyzing the relationship between the human genetic code and visible characteristics, diseases, and behaviors, among others. The aim of this study is to improve the prediction of eye color from genotype by means of several Machine Learning models, using a dataset of 308 volunteers from Buenos Aires, Argentina. The results achieved are competitive and demonstrate the usefulness of artificial intelligence (AI) in the fields of genetics and its application in areas such as health, biometrics and forensics.

KW - DNA phenotyping

KW - Eye color prediction

KW - Forensic DNA

KW - Machine Learning

UR - https://www.scopus.com/pages/publications/105007598452

U2 - 10.1016/j.compbiomed.2025.110404

DO - 10.1016/j.compbiomed.2025.110404

M3 - Artículo

C2 - 40499371

AN - SCOPUS:105007598452

SN - 0010-4825

VL - 194

JO - Computers in Biology and Medicine

JF - Computers in Biology and Medicine

M1 - 110404

ER -

DNA-based prediction of eye color in Latin American population applying Machine Learning models

Resumen

Acceder al documento

Otros archivos y enlaces

Huella

Citar esto