EpiDiP/NanoDiP: a versatile unsupervised machine learning edge computing platform for epigenomic tumour diagnostics

EpiDiP/NanoDiP: a versatile unsupervised machine learning edge computing platform for epigenomic tumour diagnostics

Abstract DNA methylation analysis based on supervised machine learning algorithms with static reference data, allowing diagnostic tumour typing with unprecedented precision, has quickly become a new standard of care. Whereas genome-wide diagnostic methylation profiling is mostly performed on microar...

Full description

Bibliographic Details
Main Authors: Jürgen Hench, Claus Hultschig, Jon Brugger, Luigi Mariani, Raphael Guzman, Jehuda Soleman, Severina Leu, Miles Benton, Irenäus Maria Stec, Ivana Bratic Hench, Per Hoffmann, Patrick Harter, Katharina J Weber, Anne Albers, Christian Thomas, Martin Hasselblatt, Ulrich Schüller, Lisa Restelli, David Capper, Ekkehard Hewer, Joachim Diebold, Danijela Kolenc, Ulf C. Schneider, Elisabeth Rushing, Rosa della Monica, Lorenzo Chiariotti, Martin Sill, Daniel Schrimpf, Andreas von Deimling, Felix Sahm, Christian Kölsche, Markus Tolnay, Stephan Frank
Format: Article
Language:English
Published: BMC 2024-04-01
Series:Acta Neuropathologica Communications
Subjects:
Digital pathology
Tumour
Oncology
Methylation
Methylome
Unsupervised machine learning
Online Access:https://doi.org/10.1186/s40478-024-01759-2

Internet

https://doi.org/10.1186/s40478-024-01759-2

Similar Items