Predicting patient-specific enhancer-promoter interactions

Brittany Baur; Sushmita Roy

doi:10.1016/j.crmeth.2023.100594

Predicting patient-specific enhancer-promoter interactions

Cell Rep Methods. 2023 Sep 25;3(9):100594. doi: 10.1016/j.crmeth.2023.100594.

Authors

Brittany Baur¹, Sushmita Roy²

Affiliations

¹ Wisconsin Institute for Discovery, 330 N. Orchard Street, Madison, WI 53715, USA; The Max Harry Weil Institute of Critical Care Research & Innovation, University of Michigan, Ann Arbor, MI, USA; Department of Emergency Medicine, University of Michigan Medical School, Ann Arbor, MI, USA.
² 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: [email protected].

Abstract

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.

Publication types

Research Support, N.I.H., Extramural
Comment

MeSH terms

Chromatin* / genetics
Humans
Patients
Precision Medicine
Promoter Regions, Genetic / genetics
Regulatory Sequences, Nucleic Acid*

Substances

Chromatin

Abstract

Publication types

MeSH terms

Substances

Grants and funding