3 citations
,
November 2022 in “European Journal of Human Genetics” This study developed new genetic prediction models for male pattern baldness with improved accuracy by utilizing a large set of markers and independent datasets, making them the most reliable available for this trait.
133 citations
,
February 2017 in “PLoS Genetics” In this study, researchers used genetic data from over 52,000 men to identify over 250 genetic loci associated with severe hair loss and developed a predictive algorithm for determining hair loss risk.
5 citations
,
November 2020 in “Forensic Science International Genetics” This study found that using trait prevalence-informed priors may improve the prediction accuracy of appearance traits in Bayesian models, but their application is limited by sparse knowledge on trait prevalence.
This review discusses forensic DNA phenotyping and its potential applications, particularly for human identification in Latin American populations, but notes challenges due to genetic diversity and reports no new results.
5 citations
,
August 2016 in “bioRxiv (Cold Spring Harbor Laboratory)” In this study, researchers identified over 250 new genetic loci linked to severe male pattern baldness, and developed a prediction algorithm that could accurately differentiate between those with severe and no hair loss.