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Вміст надано Roman Cheplyaka. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Roman Cheplyaka або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.
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#30 Bayesian inference of chromatin structure from Hi-C data with Simeon Carstens
Manage episode 228173304 series 1537951
Вміст надано Roman Cheplyaka. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Roman Cheplyaka або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.
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.
70 епізодів
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Manage episode 228173304 series 1537951
Вміст надано Roman Cheplyaka. Весь вміст подкастів, включаючи епізоди, графіку та описи подкастів, завантажується та надається безпосередньо компанією Roman Cheplyaka або його партнером по платформі подкастів. Якщо ви вважаєте, що хтось використовує ваш захищений авторським правом твір без вашого дозволу, ви можете виконати процедуру, описану тут https://uk.player.fm/legal.
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.
70 епізодів
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Схожі до the bioinformatics chat
How can we, humans, look at our relationship to nature differently? In season three of Going Wild, on top of stories about animals, we invite you to journey through the entire ecological web — from the tiniest of life forms to apex predators — alongside the scientists, activists and adventurers who study it. Wildlife biologist and host Dr. Rae Wynn-Grant has been studying wild animals in their natural habitats all over the world for years. Our award-winning podcast takes you inside the hidde ...
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continue reading
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Player FM - додаток Podcast
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