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Title : Transcriptomic analysis leads to the study of mRNA half-life and cell subtypes

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Abstract : mRNA is transcribed in the nucleus, transported to the cytoplasm, translated and degraded. The amount of mRNAs is controlled through the regulation of the transcription rate and the degradation rate. However, there is no direct way to calculate the degradation rate. To obtain the mRNA degradation rate, I used the sequencing of nascent RNAs (using global run-on sequencing (GROseq)) and total RNAs (RNAseq) in murine adipocytes. Applying a signal processing approach, I calculated mRNA half-life in adipocytes. Interestingly, I found that mRNA half-life is calculated upon the external signals. We further discuss the mechanisms that regulate mRNA stability.

As a second topic, I present an approach to study cell sub-types using single cell RNAseq data. Studying the characteristic pattern of gene expression across single cells, the proposed approach can perform sub-type clustering without normalization.

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Bio

1996 Áß¾Ó´ëÇб³ ÀüÀÚ°øÇаú ¼®»ç

1999 Áß¾Ó´ëÇб³ ÀüÀÚ°øÇаú ¼®»ç (Artificial Intelligence (AI))

2005 Ph.D. in Electronics and Computer Science, (AI for biological data analysis)

University of Southampton, Southampton, UK

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1999-2001 Dept. of Information and Technology,

National University of Hanoi, Vietnam (database administration)

2006 Postdoctoral Fellow, Bioinformatics Center, University of Copenhagen

2007-2010 Postdoctoral Fellow, Dept of Chemistry & Biochemistry (Epigenomics)

University of California, San Diego (UCSD)

2011- Research Assistant Professor, (Computational biology)

Perelman School of Medicine, University of Pennsyvania

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