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Ki-Sun Park

Researcher at National Institutes of Health

Publications -  9
Citations -  301

Ki-Sun Park is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Genomic imprinting & Phosphorylation. The author has an hindex of 5, co-authored 8 publications receiving 233 citations. Previous affiliations of Ki-Sun Park include New Generation University College & Seoul National University.

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MIR144* inhibits antimicrobial responses against Mycobacterium tuberculosis in human monocytes and macrophages by targeting the autophagy protein DRAM2

TL;DR: This study shows that Mtb significantly induces the expression of MIR144*/hsa-miR-144-5p, which targets the 3′-untranslated region of DRAM2 (DNA damage regulated autophagy modulator 2) in human monocytes and macrophages, and reveals that DR AM2 is a key coordinator of autophagic activation that enhances antimicrobial activity against Mtb.
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Circular RNAs and competing endogenous RNA (ceRNA) networks.

TL;DR: In recent years, advances in bioinformatics approaches have allowed a systematic characterization of circular RNAs across a variety of cell types, and investigators have begun focusing on the possibility that circRNAs operate as part of competing endogenous RNA (ceRNA) regulatory networks.
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Loss of imprinting mutations define both distinct and overlapping roles for misexpression of IGF2 and of H19 lncRNA.

TL;DR: New biochemical roles for the H19 lncRNA are identified and it is underscored that LOI phenotypes are multigenic so that complex interactions will contribute to disease outcomes.
Posted ContentDOI

Genetic discovery and translational decision support from exome sequencing of 20,791 type 2 diabetes cases and 24,440 controls from five ancestries

Jason Flannick, +179 more
- 31 Jul 2018 - 
TL;DR: An exome sequence analysis of type 2 diabetes cases and controls presents a Bayesian framework to recalibrate association p-values as posterior probabilities of association, estimating that reaching p<0.05 in this study increases the odds of causal T2D association for a nonsynonymous variant by a factor of 1.3.