J
Jen-Tsan Chi
Researcher at Duke University
Publications - 131
Citations - 10324
Jen-Tsan Chi is an academic researcher from Duke University. The author has contributed to research in topics: Gene expression profiling & Cancer. The author has an hindex of 43, co-authored 121 publications receiving 8651 citations. Previous affiliations of Jen-Tsan Chi include Durham University & Stanford University.
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Journal ArticleDOI
KEAP1 has a sweet spot: A new connection between intracellular glycosylation and redox stress signaling in cancer cells.
TL;DR: It is discovered that NRF2 signaling is controlled by the site-specific glycosylation of KEAP1, revealing a potentially broad link among nutrient sensing, proteostasis and stress resistance in both normal and cancer cells.
Journal ArticleDOI
Discovery, Genomic Analysis, and Functional Role of the Erythrocyte RNAs
TL;DR: A strong case is provided for the translational potential and functional relevance of these erythrocyte transcripts and conceptual frameworks for the future works on other potential applications of the ery Throcyte transcriptome are provided.
Patent
Methods and compositions for the treatment of erythrocyte diseases
TL;DR: In this article, the miRNA compositions can also be used to determine the severity of erythrocyte disease, and the features and clinical phenotypes of the different types of disorders.
ComponentDOI
Mammalian stringent-like response mediated by the cytosolic NADPH phosphatase MESH1
TL;DR: It is reported that human MESH1 is an efficient cytosolic NADPH phosphatase, an unexpected enzymatic activity that is captured by the crystal structure of the Mesh1-NADPH complex, implicating MESH 1 in a previously uncharacterized stress response in mammalian cells.
Journal ArticleDOI
Single Cell RNA-Seq Analysis of Human Red Cells
TL;DR: Single cell RNA-Seq is performed to analyze the transcriptional heterogeneity of RBCs from three adult healthy donors which have been stored in the blood bank conditions and assayed at day 1 and day 15 to indicate the power of single RBC RNA- Seq to capture and discover known and unexpected heterogeneity ofRBC population.