ArticleBMC bioinformatics2011
Predicting gene expression in T cell differentiation from histone modifications and transcription factor binding affinities by linear mixture models.
Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Article
- Accurate and highly interpretable prediction of gene expression from histone modifications.BMC bioinformatics · 2022Article
- Functional effects of variation in transcription factor binding highlight long-range gene regulation by epromoters.Nucleic acids research · 2020Article
- A comprehensive review of computational prediction of genome-wide features.Briefings in bioinformatics · 2020Article
- Bayesian mixture regression analysis for regulation of Pluripotency in ES cells.BMC bioinformatics · 2020Article
- On the problem of confounders in modeling gene expression.Bioinformatics (Oxford, England) · 2019Review
- Prediction of Gene Expression Patterns With Generalized Linear Regression Model.Frontiers in genetics · 2019Article
- Revealing transcription factor and histone modification co-localization and dynamics across cell lines by integrating ChIP-seq and RNA-seq data.BMC genomics · 2018Article
- The HTPmod Shiny application enables modeling and visualization of large-scale biological data.Communications biology · 2018Article
- RegulatorTrail: a web service for the identification of key transcriptional regulators.Nucleic acids research · 2017Article
- Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction.Nucleic acids research · 2017Article
- Differential peak calling of ChIP-seq signals with replicates with THOR.Nucleic acids research · 2016Article
- Bayesian immunological model development from the literature: example investigation of recent thymic emigrants.Journal of immunological methods · 2014Article
- Human Transcriptome and Chromatin Modifications: An ENCODE Perspective.Genomics & informatics · 2013Article
- Modeling gene expression using chromatin features in various cellular contexts.Genome biology · 2012Article
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4 authors.
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Abstract
backgroundThe differentiation process from stem cells to fully differentiated cell types is controlled by the interplay of chromatin modifications and transcription factor activity. Histone modifications or transcription factors frequently act in a multi-functional manner, with a given DNA motif or histone modification conveying both transcriptional repression and activation depending on its location in the promoter and other regulatory signals surrounding it.
resultsTo account for the possible multi functionality of regulatory signals, we model the observed gene expression patterns by a mixture of linear regression models. We apply the approach to identify the underlying histone modifications and transcription factors guiding gene expression of differentiated CD4+ T cells. The method improves the gene expression prediction in relation to the use of a single linear model, as often used by previous approaches. Moreover, it recovered the known role of the modifications H3K4me3 and H3K27me3 in activating cell specific genes and of some transcription factors related to CD4+ T differentiation.
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