Deciphering 3D organization of chromosomes using Hi-C data
Author(s)
Hofmann, A
Heermann, DW
Griffith University Author(s)
Year published
2018
Metadata
Show full item recordAbstract
In order to interpret data from Hi-C studies genome-wide contact probability maps need to be translated into models of functional 3D genome organization. Here, we first present an overview of computational methods to analyze contact probability maps in terms of features such as the level and shape of compartmentalization. Next, we describe approaches to modeling 3D genome organization based on Hi-C data.In order to interpret data from Hi-C studies genome-wide contact probability maps need to be translated into models of functional 3D genome organization. Here, we first present an overview of computational methods to analyze contact probability maps in terms of features such as the level and shape of compartmentalization. Next, we describe approaches to modeling 3D genome organization based on Hi-C data.
View less >
View less >
Book Title
Methods in Molecular Biology
Volume
1837
Subject
Other chemical sciences
Biological sciences
Biochemistry and cell biology