#30 Bayesian inference of chromatin structure from Hi-C data with Simeon Carstens

Hi-C is a sequencing-based assay that provides information about the 3-dimensional organization of the genome.
In this episode, Simeon Carstens explains how he
applied the Inferential Structure Determination (ISD) framework to build a 3D
model of chromatin and fit that model to Hi-C data using Hamiltonian Monte
Carlo and Gibbs sampling.




Links:


Bayesian inference of chromatin structure ensembles from population Hi-C data (Simeon Carstens, Michael Nilges, Michael Habeck)
Inferential Structure Determination of Chromosomes from Single-Cell Hi-C Data (Simeon Carstens, Michael Nilges, Michael Habeck)





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