Predicting patient-specific enhancer-promoter interactions.

Cell Rep Methods

Wisconsin Institute for Discovery, 330 N. Orchard Street, Madison, WI 53715, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53715, USA. Electronic address:

Published: September 2023

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.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10545932PMC
http://dx.doi.org/10.1016/j.crmeth.2023.100594DOI Listing

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Predicting patient-specific enhancer-promoter interactions.

Cell Rep Methods

September 2023

Wisconsin Institute for Discovery, 330 N. Orchard Street, Madison, WI 53715, USA; Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, WI 53715, USA. Electronic address:

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.

View Article and Find Full Text PDF

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