#30 Bayesian inference of chromatin structure from Hi-C data with Simeon Carstens - a podcast by Roman Cheplyaka
from 2019-02-27T19:00
::
::
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)
If you enjoyed this episode, please consider supporting the podcast on Patreon.
Further episodes of the bioinformatics chat
Further podcasts by Roman Cheplyaka
Website of Roman Cheplyaka