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Yeji Lee

Researcher at University of Michigan

Publications -  5
Citations -  973

Yeji Lee is an academic researcher from University of Michigan. The author has contributed to research in topics: Genome-wide association study & Chemistry. The author has an hindex of 2, co-authored 2 publications receiving 786 citations.

Papers
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Journal ArticleDOI

An Expanded Genome-Wide Association Study of Type 2 Diabetes in Europeans

Robert A. Scott, +216 more
- 01 Nov 2017 - 
TL;DR: This article conducted a meta-analysis of genome-wide association data from 26,676 T2D case and 132,532 control subjects of European ancestry after imputation using the 1000 Genomes multiethnic reference panel.
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Genetic fine mapping and genomic annotation defines causal mechanisms at type 2 diabetes susceptibility loci

Kyle J. Gaulton, +261 more
- 01 Dec 2015 - 
TL;DR: This paper performed fine mapping of 39 established type 2 diabetes (T2D) loci in 27,206 cases and 57,574 controls of European ancestry, and identified 49 distinct association signals at these loci including five mapping in or near KCNQ1.
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Structural and functional characterization of TrmM in m6A modification of bacterial tRNA

TL;DR: The results reveal that the dimeric form of M. capricolum TrmM is important for efficient tRNA binding and catalysis, thereby offering insights into the distinct substrate specificity of the monomeric E. coli homolog.
Proceedings ArticleDOI

Prediction of Chemotherapy-Induced Neutropenia using Machine Learning in Cancer Patients

TL;DR: In this article , the authors predicted neutropenia 48 hours in advance of adult cancer patients who were prescribed cytotoxic drugs using two neural network models: Bi-LSTM and RTAIN.
Journal ArticleDOI

CAGCN: Causal attention graph convolutional network against adversarial attacks

Yeji Lee, +1 more
- 01 Mar 2023 - 
TL;DR: Zhang et al. as mentioned in this paper proposed a causal attention graph convolutional network (CAGCN) which uses two types of attention, node attention (NoA) and neighbor attention (NeA), to detect DDoS attacks.