Computers in biology and medicine. 2025 Jun 10:194:110404. doi: 10.1016/j.compbiomed.2025.110404 Q17.02024

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

基于机器学习模型的应用于拉丁美洲人群的DNA眼色预测研究翻译改进

Cristian A Martínez¹, Diana M Hohl², María de Los A Gutiérrez³, Sagnik Palmal⁴, Pierre Faux⁵, Kaustubh Adhikari⁶, Rolando Gonzalez-Jose⁷, Maria C Bortolini⁸, Victor Acuña-Alonzo⁹, Carla Gallo¹⁰, Andres Ruiz Linares¹¹, Francisco Rothhammer¹², Cecilia I Catanesi¹³, Ricardo J Barrientos¹⁴

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作者单位

¹ Lab. LITRP, Depto. DCI, Facultad de Ciencias de la Ingeniería, Universidad Católica del Maule, Av. San Miguel 3605, Talca, 3480112, Chile. Electronic address: cmartinez@di.unsa.edu.ar.

² Lab. de Diversidad Genética, Instituto Multidisciplinario de Biología Celular (CONICET-UNLP-CICPBA), Av. 526 y Camino Gral. Belgrano, La Plata, 1900, Buenos Aires, Argentina; Comisión de Investigaciones Científicas de la Provincia de Buenos Aires CICPBA, Av. 526 entre 10 y 11, La Plata, 1900, Buenos Aires, Argentina.

³ Centro de Investigaciones del Medio Ambiente (CONICET-UNLP-CICPBA), Boulevard 120 N(o) 1489, La Plata, 1900, Buenos Aires, Argentina.

⁴ Université de Lille, INSERM, CHU Lille, institut pasteur de Lille, U1167-RID-AGE, Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France.

⁵ GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet Tolosan, France.

⁶ School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, MK7 6AA, United Kingdom.

⁷ Instituto Patagónico de Ciencias Sociales y Humanas, Centro Nacional Patagónico, CONICET, Bv. Almirante Brown 2915, Puerto Madryn, U9120ACD, Chubut, Argentina.

⁸ Instituto de Biociências, Universidad Federal do Rio Grande do Sul, Av. Paulo Gama 110, Porto Alegre, 90040-060, Rio Grande do Sul, Brazil.

⁹ National Institute of Anthropology and History, 135 Hamburgo, Mexico City, 06600, Mexico.

¹⁰ Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofía, Universidad Peruana Cayetano Heredia, Av. Honorio Delgado 430, Lima, 15102, Peru.

¹¹ Ministry of Education Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center of Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, 220 Handan Road, Shanghai, 200434, China; ADES (Anthropologie Bio-Culturelle, Droit, Éthique et Santé), UFR de Médecine, Aix-Marseille University, 58 Blvd Charles Livon, Marseille, 13007, France; Department of Genetics, Evolution and Environment and UCL Genetics Institute, University College London, London, WC1E 6BT, United Kingdom.

¹² Instituto de Alta Investigación, Tarapacá University, 2222 18 de Septiembre Av, Arica, 1000000, Chile.

¹³ Lab. de Diversidad Genética, Instituto Multidisciplinario de Biología Celular (CONICET-UNLP-CICPBA), Av. 526 y Camino Gral. Belgrano, La Plata, 1900, Buenos Aires, Argentina; Facultad de Ciencias Naturales y Museo, Universidad Nacional de La Plata, Calle 122 y 60, La Plata, 1900, Buenos Aires, Argentina.

¹⁴ Lab. LITRP, Depto. DCI, Facultad de Ciencias de la Ingeniería, Universidad Católica del Maule, Av. San Miguel 3605, Talca, 3480112, Chile.

DOI: 10.1016/j.compbiomed.2025.110404 PMID: 40499371

摘要中英对照阅读

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.

Keywords：DNA based prediction; Eye color; Latin American population; Machine Learning models

基因组测序和基因分型成本的降低使得能够更广泛地使用数据库来分析人类遗传密码与外貌特征、疾病和行为等之间的关系。本研究旨在通过几种机器学习模型，利用来自阿根廷布宜诺斯艾利斯308名志愿者的数据集，改进从基因型预测眼睛颜色的方法。所取得的结果具有竞争力，并展示了人工智能在遗传学领域及其在健康、生物识别和法医等领域应用中的实用性。

关键词： 基因表型分析；眼睛颜色预测；法医DNA；机器学习。

关键词：基于DNA的预测; 眼色; 拉丁美洲人口; 机器学习模型

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期刊名：Computers in biology and medicine

缩写：COMPUT BIOL MED

ISSN：0010-4825

e-ISSN：1879-0534

IF/分区：7.0/Q1

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

基于机器学习模型的应用于拉丁美洲人群的DNA眼色预测研究翻译改进

[The population of Latin America]

[拉丁美洲的人口]

The Second Latin American Population Conference

第二届拉丁美洲人口大会

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

基于机器学习模型的应用于拉丁美洲人群的DNA眼色预测研究 翻译改进

[The population of Latin America]

[拉丁美洲的人口]

The Second Latin American Population Conference

第二届拉丁美洲人口大会

The effect of descriptor choice in machine learning models for ionic liquid melting point prediction

机器学习模型中描述符选择对离子液体熔点预测的影响

Evaluation of machine learning models that predict lncRNA subcellular localization

评估预测长链非编码RNA亚细胞定位的机器学习模型

EVMP: enhancing machine learning models for synthetic promoter strength prediction by Extended Vision Mutant Priority framework

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基于机器学习模型的应用于拉丁美洲人群的DNA眼色预测研究翻译改进