Cargando…
Investigating the effect of dependence between conditions with Bayesian Linear Mixed Models for motif activity analysis
MOTIVATION: Cellular identity and behavior is controlled by complex gene regulatory networks. Transcription factors (TFs) bind to specific DNA sequences to regulate the transcription of their target genes. On the basis of these TF motifs in cis-regulatory elements we can model the influence of TFs o...
Autores principales: | Lederer, Simone, Heskes, Tom, van Heeringen, Simon J., Albers, Cornelis A. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7194367/ https://www.ncbi.nlm.nih.gov/pubmed/32357166 http://dx.doi.org/10.1371/journal.pone.0231824 |
Ejemplares similares
-
Additive Dose Response Models: Explicit Formulation and the Loewe Additivity Consistency Condition
por: Lederer, Simone, et al.
Publicado: (2018) -
Bayesian Estimation of Conditional Independence Graphs Improves Functional Connectivity Estimates
por: Hinne, Max, et al.
Publicado: (2015) -
GimmeMotifs: a de novo motif prediction pipeline for ChIP-sequencing experiments
por: van Heeringen, Simon J., et al.
Publicado: (2011) -
Additive Dose Response Models: Defining Synergy
por: Lederer, Simone, et al.
Publicado: (2019) -
Polygenic Modeling with Bayesian Sparse Linear Mixed Models
por: Zhou, Xiang, et al.
Publicado: (2013)