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

Institute of Higher Research

Universidad Católica del Maule
Consejo Nacional de Investigaciones Científicas y Técnicas
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
Université de Lille
Université Fédérale Toulouse Midi-Pyrénées
Open University Milton Keynes
Universidade Federal do Rio Grande do Sul
National Institute of Anthropology and History
Universidad Peruana Cayetano Heredia
Fudan University
ADES
University College London
Universidad Nacional de La Plata

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

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.

Original language	English
Article number	110404
Journal	Computers in Biology and Medicine
Volume	194
DOIs	https://doi.org/10.1016/j.compbiomed.2025.110404
State	Published - Aug 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Keywords

DNA phenotyping
Eye color prediction
Forensic DNA
Machine Learning

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10.1016/j.compbiomed.2025.110404

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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, Article 110404. https://doi.org/10.1016/j.compbiomed.2025.110404

@article{772d8feba604474a83570f7c5f665c7e,

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 = "English",

volume = "194",

journal = "Computers in Biology and Medicine",

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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 - Article

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

Abstract

UN SDGs

Keywords

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