A Genome-Wide Association Study and Machine-Learning Algorithm Analysis on the Prediction of Facial Phenotypes by Genotypes in Korean Women.
Yoo HY, Lee KC, Woo JE et al.
Publication Details
Comprehensive information about this research publication
Abstract
Summary of the research findings
Purpose: Changes in facial appearance are affected by various intrinsic and extrinsic factors, which vary from person to person. Therefore, each person needs to determine their skin condition accurately to care for their skin accordingly. Recently, genetic identification by skin-related phenotypes has become possible using genome-wide association studies (GWAS) and machine-learning algorithms. However, because most GWAS have focused on populations with American or European skin pigmentation, large-scale GWAS are needed for Asian populations. This study aimed to evaluate the correlation of facial phenotypes with candidate single-nucleotide polymorphisms (SNPs) to predict phenotype from genotype using machine learning.
730 Korean ancestry individuals
Study Statistics
Key metrics and study information
Analysis
Comprehensive review of health and genetic findings
Important Disclaimer: This review has been performed semi-automatically and is provided for informational purposes only. While we strive for accuracy, this analysis may contain errors, omissions, or misinterpretations of the original research. DNA Genics disclaims all liability for any inaccuracies, errors, or consequences arising from the use of this information. Users should independently verify all information and consult original research publications before making any decisions based on this content. This analysis is not intended as a substitute for professional scientific review or medical advice.
Analysis In Progress
Our analysis of this publication is currently being prepared. Please check back soon for comprehensive insights into the health and genetic findings discussed in this research.