Integrative analysis of deep sequencing data identifies estrogen receptor early response genes and links ATAD3B to poor survival in breast cancer.
Identification of responsive genes to an extra-cellular cue enables characterization of pathophysiologically crucial biological processes. Deep sequencing technologies provide a powerful means to identify responsive genes, which creates a need for computational methods able to analyze dynamic and mu...
Main Authors: | Kristian Ovaska, Filomena Matarese, Korbinian Grote, Iryna Charapitsa, Alejandra Cervera, Chengyu Liu, George Reid, Martin Seifert, Hendrik G Stunnenberg, Sampsa Hautaniemi |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2013-01-01
|
Series: | PLoS Computational Biology |
Online Access: | http://europepmc.org/articles/PMC3688481?pdf=render |
Similar Items
-
Predicting stimulation-dependent enhancer-promoter interactions from ChIP-Seq time course data
by: Tomasz Dzida, et al.
Published: (2017-09-01) -
Fast Gene Ontology based clustering for microarray experiments
by: Ovaska Kristian, et al.
Published: (2008-11-01) -
Etudes des ATPases AAA+ ATAD3A et ATAD3B
by: Merle, Nicolas
Published: (2011) -
Etudes des ATPases AAA+ ATAD3A et ATAD3B
by: Merle, Nicolas
Published: (2011) -
Inference of RNA polymerase II transcription dynamics from chromatin immunoprecipitation time course data.
by: Ciira wa Maina, et al.
Published: (2014-05-01)