A supervised learning method for classifying methylation disorders

A supervised learning method for classifying methylation disorders

Abstract Background DNA methylation is one of the most stable and well-characterized epigenetic alterations in humans. Accordingly, it has already found clinical utility as a molecular biomarker in a variety of disease contexts. Existing methods for clinical diagnosis of methylation-related disorder...

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Bibliographic Details
Main Authors: Jesse R. Walsh, Guangchao Sun, Jagadheshwar Balan, Jayson Hardcastle, Jason Vollenweider, Calvin Jerde, Kandelaria Rumilla, Christy Koellner, Alaa Koleilat, Linda Hasadsri, Benjamin Kipp, Garrett Jenkinson, Eric Klee
Format: Article
Language:English
Published: BMC 2024-02-01
Series:BMC Bioinformatics
Subjects:
Congenital disease
Methylation
Diagnosis
Machine learning
Angelman syndrome
Prader–Willi syndrome
Online Access:https://doi.org/10.1186/s12859-024-05673-1

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