Benefiting from the intrinsic role of epigenetics to predict patterns of CTCF binding.
Binding Prediction
CTCF
Histone Marks
Random Forests
Journal
Computational and structural biotechnology journal
ISSN: 2001-0370
Titre abrégé: Comput Struct Biotechnol J
Pays: Netherlands
ID NLM: 101585369
Informations de publication
Date de publication:
2023
2023
Historique:
received:
19
12
2022
revised:
11
05
2023
accepted:
11
05
2023
medline:
2
6
2023
pubmed:
2
6
2023
entrez:
2
6
2023
Statut:
epublish
Résumé
One of the most relevant mechanisms involved in the determination of chromatin structure is the formation of structural loops that are also related with the conservation of chromatin states. Many of these loops are stabilized by CCCTC-binding factor (CTCF) proteins at their base. Despite the relevance of chromatin structure and the key role of CTCF, the role of the epigenetic factors that are involved in the regulation of CTCF binding, and thus, in the formation of structural loops in the chromatin, is not thoroughly understood. Here we describe a CTCF binding predictor based on Random Forest that employs different epigenetic data and genomic features. Importantly, given the ability of Random Forests to determine the relevance of features for the prediction, our approach also shows how the different types of descriptors impact the binding of CTCF, confirming previous knowledge on the relevance of chromatin accessibility and DNA methylation, but demonstrating the effect of epigenetic modifications on the activity of CTCF. We compared our approach against other predictors and found improved performance in terms of areas under PR and ROC curves (PRAUC-ROCAUC), outperforming current state-of-the-art methods.
Identifiants
pubmed: 37266407
doi: 10.1016/j.csbj.2023.05.012
pii: S2001-0370(23)00194-0
pmc: PMC10229758
doi:
Types de publication
Journal Article
Langues
eng
Pagination
3024-3031Informations de copyright
© 2023 The Authors.
Déclaration de conflit d'intérêts
None declared.
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