ArticleMedizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V2021
Technologies for profiling the impact of genomic variants on transcription factor binding.
Article in Medizinische Genetik : Mitteilungsblatt des Berufsverbandes Medizinische Genetik e.V, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Discovery of a non-canonical GRHL1 binding site using deep convolutional and recurrent neural networks.BMC genomics · 2023Article
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5 authors.
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Abstract
Transcription factors (TFs) bind DNA in a sequence-specific manner and thereby regulate target gene expression. TF binding and its regulatory activity is highly context dependent, and is not only determined by specific cell types or differentiation stages but also relies on other regulatory mechanisms, such as DNA and chromatin modifications. Interactions between TFs and their DNA binding sites are critical mediators of phenotypic variation and play important roles in the onset of disease. A continuously growing number of studies therefore attempts to elucidate TF:DNA interactions to gain knowledge about regulatory mechanisms and disease-causing variants. Here we summarize how TF-binding characteristics and the impact of variants can be investigated, how bioinformatic tools can be used to analyze and predict TF:DNA binding, and what additional information can be obtained from the TF protein structure.
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