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Related Experiment Video

Updated: Jun 14, 2025

Rapid Genetic Analysis of Epithelial-Mesenchymal Signaling During Hair Regeneration
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Deep Hair Phenomics: Implications in Endocrinology, Development, and Aging.

Jasson Makkar1, Jorge Flores1, Mason Matich1

  • 1School of Molecular Biosciences, Washington State University, Pullman, Washington, USA.

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We developed a deep learning tool to precisely measure hair traits like length and color. This high-throughput hair phenomics approach aids in understanding health and disease through fur analysis.

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Area of Science:

  • Biomedical Science
  • Computer Vision
  • Genetics

Background:

  • Hair quality is a key health indicator, but current assessment methods are limited in throughput and quantification.
  • Assessing individual hair fiber characteristics is challenging due to technical limitations.

Purpose of the Study:

  • To develop a high-throughput, quantitative method for analyzing individual hair fibers using deep learning and computer vision.
  • To explore the impact of hormonal signaling, genetic modifications, and aging on hair follicle output and hair phenotypes.

Main Methods:

  • A novel deep learning-based computer vision approach was created to quantify individual hair fibers.
  • The tool can distinguish and extract overlapping fibers for multivariate feature analysis (length, width, color).
  • Applied the tool to analyze hair phenotypes in mice across different conditions and life stages.

Main Results:

  • Generated high-resolution, single-hair phenomes, revealing diverse hair conditions.
  • Identified hair phenotypes associated with hormonal, developmental, and aging-related alterations in mouse fur.
  • Demonstrated the tool's efficacy in characterizing factors that modulate hair follicles.

Conclusions:

  • The developed deep hair phenomics tool offers a high-throughput solution for quantitative hair analysis.
  • This technology enables the characterization of factors influencing hair follicle biology.
  • The approach shows potential for novel diagnostic methods by analyzing hair fibers for disease detection.