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Predicting patient-specific enhancer-promoter interactions

Computational methods that can predict hard-to-measure modalities from those that are easier to measure, in a patient-specific manner, play a critical role in personalized medicine. In this issue of Cell Reports Methods, Khurana et al. present differential gene targets of accessible chromatin (DGTAC...

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Detalles Bibliográficos
Autores principales: Baur, Brittany, Roy, Sushmita
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10545932/
https://www.ncbi.nlm.nih.gov/pubmed/37751694
http://dx.doi.org/10.1016/j.crmeth.2023.100594
Descripción
Sumario:Computational methods that can predict hard-to-measure modalities from those that are easier to measure, in a patient-specific manner, play a critical role in personalized medicine. In this issue of Cell Reports Methods, Khurana et al. present differential gene targets of accessible chromatin (DGTAC), an approach which predicts patient-specific enhancer-promoter interactions.