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Titel:

A deep learning method for replicate-based analysis of chromosome conformation contacts using Siamese neural networks.

Dokumenttyp:
Journal Article; Research Support, Non-U.S. Gov't
Autor(en):
Al-Jibury, Ediem; King, James W D; Guo, Ya; Lenhard, Boris; Fisher, Amanda G; Merkenschlager, Matthias; Rueckert, Daniel
Abstract:
The organisation of the genome in nuclear space is an important frontier of biology. Chromosome conformation capture methods such as Hi-C and Micro-C produce genome-wide chromatin contact maps that provide rich data containing quantitative and qualitative information about genome architecture. Most conventional approaches to genome-wide chromosome conformation capture data are limited to the analysis of pre-defined features, and may therefore miss important biological information. One constraint...     »
Zeitschriftentitel:
Nat Commun
Jahr:
2023
Band / Volume:
14
Heft / Issue:
1
Volltext / DOI:
doi:10.1038/s41467-023-40547-9
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/37591842
Print-ISSN:
2041-1723
TUM Einrichtung:
Institut für KI und Informatik in der Medizin (Prof. Rückert)
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