A computational pipeline to learn gene expression predictive models from epigenetic information at enhancers or promoters-Reference-Cited by-同舟云学术

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A computational pipeline to learn gene expression predictive models from epigenetic information at enhancers or promoters

Published:2023-03 Issue:1 Volume:4 Page:101948
ISSN:2666-1667
Container-title:STAR Protocols
language:en
Short-container-title:STAR Protocols

Author:

González-Ramírez Mar,Blanco Enrique,Di Croce Luciano^ORCID

Publisher

Elsevier BV

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Neuroscience

Reference29 articles.

1. Differential contribution to gene expression prediction of histone modifications at enhancers or promoters;González-Ramírez;PLoS Comput. Biol.,2021

2. R: A Language and Environment for Statistical Computing,2020

3. RStudio: Integrated Development Environment for R,2020

4. Python 3 Reference Manual;Van Rossum,2009

5. EPOP functionally links elongin and polycomb in pluripotent stem cells;Beringer;Mol. Cell,2016

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