Integrative analysis of histone ChIP-seq and transcription data using Bayesian mixture models | Zendy

HansUlrich Klein | Zendy; Martin Schäfer | Zendy; Bo Porse | Zendy; Marie Sigurd Hasemann | Zendy; Katja Ickstadt | Zendy; Martin Dugas | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

Integrative analysis of histone ChIP-seq and transcription data using Bayesian mixture models

Author(s) -

HansUlrich Klein,

Martin Schäfer,

Bo Porse,

Marie Sigurd Hasemann,

Katja Ickstadt,

Martin Dugas

Publication year - 2014

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btu003

Subject(s) - bioconductor , computational biology , histone , dna microarray , epigenetics , normalization (sociology) , bayesian probability , biology , epigenomics , gene , genetics , computer science , gene expression , dna methylation , artificial intelligence , sociology , anthropology

Histone modifications are a key epigenetic mechanism to activate or repress the transcription of genes. Datasets of matched transcription data and histone modification data obtained by ChIP-seq exist, but methods for integrative analysis of both data types are still rare. Here, we present a novel bioinformatics approach to detect genes that show different transcript abundances between two conditions putatively caused by alterations in histone modification.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research