基于单倍群的方法,利用 Y-STR 数据将个体归入地理区域

IF 2.2 3区 医学 Q1 MEDICINE, LEGAL
Marziyeh Afkanpour , Mehri Momeni , Arash Alipour Tabrizi , Hamed Tabesh
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引用次数: 0

摘要

Y 染色体标记是法医遗传学的重要工具,为基因鉴定提供了宝贵的见解。本研究试图利用机器学习技术开发一个法医预测模型,以提高基因鉴定过程的效率。具体来说,该模型旨在根据 Y 染色体标记分析预测个人最近的居住地理区域。该方法包括四个关键步骤:单倍群确定、主要分支识别、地理区域分配、模型分层和微调。该模型开发完成后,可集成到决策支持系统中,为法医遗传学家提供可靠的知识来源,以加强调查过程中的决策制定。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A haplogroup-based methodology for assigning individuals to geographical regions using Y-STR data
Y chromosome markers are essential tools in forensic genetics, offering valuable insights for genetic identification. This study seeks to develop a forensic prediction model using machine learning techniques to improve the efficiency of genetic identification processes. Specifically, the model aims to predict an individual's nearest geographical area of residence based on Y chromosome marker analysis. The methodology involved four key steps: haplogroup determination, primary branch identification, geographical region assignment, model stratification, and fine-tuning. Once developed, the model can be integrated into decision support systems, providing forensic geneticists with a reliable knowledge source to enhance decision-making during investigations.
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来源期刊
Forensic science international
Forensic science international 医学-医学:法
CiteScore
5.00
自引率
9.10%
发文量
285
审稿时长
49 days
期刊介绍: Forensic Science International is the flagship journal in the prestigious Forensic Science International family, publishing the most innovative, cutting-edge, and influential contributions across the forensic sciences. Fields include: forensic pathology and histochemistry, chemistry, biochemistry and toxicology, biology, serology, odontology, psychiatry, anthropology, digital forensics, the physical sciences, firearms, and document examination, as well as investigations of value to public health in its broadest sense, and the important marginal area where science and medicine interact with the law. The journal publishes: Case Reports Commentaries Letters to the Editor Original Research Papers (Regular Papers) Rapid Communications Review Articles Technical Notes.
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