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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
  • 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

Research output: Contribution to journalArticlepeer-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 languageEnglish
Article number110404
JournalComputers in Biology and Medicine
Volume194
DOIs
StatePublished - Aug 2025

Keywords

  • DNA phenotyping
  • Eye color prediction
  • Forensic DNA
  • Machine Learning

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