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ÀÛ¼ºÀÚ | °ü¸®ÀÚ | ÀÛ¼ºÀÏ | 2016-11-30 |
¼¿ï´ëÇб³ »ý¹°Á¤º¸ÇÐ Çùµ¿°úÁ¤ ÁÖÃַΠƯº° ¼¼¹Ì³ª¸¦ ¾Æ·¡¿Í °°ÀÌ ¿°íÀÚ ÇÏ¿À´Ï, ¸¹Àº Âü¿© ¹Ù¶ø´Ï´Ù. ¡¡ ÀϽÃ: 2016³â 12¿ù 07ÀÏ ¼ö¿äÀÏ ¿ÀÀü 11½Ã ¿¬»ç: ³²Áø¿ì(ÇѾç´ëÇб³ »ý¸í°úÇаú) Àå¼Ò: ¼¿ï´ëÇб³ 25µ¿ 411È£ ¡¡ Title : High-confidence Coding and Noncoding Transcriptome Maps ¡¡ Abstract : The advent of high-throughput RNA-sequencing (RNA-seq) has led to the discovery of unprecedentedly immense transcriptomes encoded by eukaryotic genomes. However, the transcriptome maps are still incomplete partly because they were mostly reconstructed based on RNA-seq reads that lack their orientations (known as unstranded reads) and certain boundary information. Methods to expand the usability of unstranded RNA-seq data by predetermining the orientation of the reads and precisely determining the boundaries of assembled transcripts could significantly benefit the quality of the resulting transcriptome maps. Here, we present a high-performing transcriptome assembly pipeline, called CAFE, that significantly improves the original assemblies, respectively assembled with stranded and/or unstranded RNA-seq data, by orienting unstranded reads using the maximum likelihood estimation and by integrating information about transcription start sites and cleavage and polyadenylation sites. Applying large-scale transcriptomic data comprising ninety-nine billion RNAs-seq reads from the ENCODE, human BodyMap projects, The Cancer Genome Atlas, and GTEx, CAFE enabled us to predict the directions of about eighty-nine billion unstranded reads, which led to the construction of more accurate transcriptome maps, comparable to the manually curated map, and a comprehensive lncRNA catalogue that includes thousands of novel lncRNAs. Our pipeline should not only help to build comprehensive, precise transcriptome maps from complex genomes but also to expand the universe of non-coding genomes. ¡¡ Education Sep, 2004. ~ Aug, 2007. Ph. D. in Bioinformatics of Seoul National University. Sep, 2002 ~ Aug, 2004. ME in Bioinformatics of Seoul National University. Mar, 1994 ~ Feb, 2001. BS in Biology of Yonsei University. ¡¡ Professional Research Experiences 2016.9~ Associate Professor, Dept. of Life Science, Hanyang University. 2014.3~2016.8 Assistant Professor, Dept. of Life Science, Hanyang University. 2012.9~2014.2 Assistant Professor, Graduate School in Biomedical Science and Engineering, Hanyang University. 2008~2012 Postdoctoral fellow, MIT, HHMI, Whitehead Institute for Biomedical Research 2007~2008 Postdoctoral fellow, Seoul National University, MicroRNA Research Center 2002~2008 Researcher, Center for Bioinformation Technology (CBIT), Seoul National University. 2003 Visiting Researcher, Short‐term Program (2 months), Sakakibara Laboratory, Keio University, Japan. Research: SNP analysis using DNA computing. 2001~2002 Research Assistant, Genome Sequencing and SNP Analysis, Corporation Pangenomics. ¡¡ Selected Publications [Peer‐reviewed Papers] Hui Kwon Kim, Myungjae Song, Jinu Lee, Adrussery. Vipin Menon, Soobin Jung, Young‐Mook Kang, Euijeon Woo, Jin‐Wu Nam, and Hyongbum (Henry) Kim. In vivo high‐throughput profiling of CRISPR‐Cpf1 activity based on target sequence composition. Nature Methods. in press. Youngjune Park, Sangsoo Lim, Jin‐Wu Nam, and Sun Kim. Measuring intratumor heterogeneity by network entropy using RNA‐seq data. Sci. Rep. 6, 37767; doi: 10.1038/srep37767 (2016). Jang‐il Sohn and Jin‐Wu Nam, The Present and Future of De Novo Whole Genome Assembly, Briefings in Bioinformatics, doi: 10.1093/bib/bbw096. 2016 Yong‐Hee Rhee, Tae‐Ho Kim, A‐Young Jo, Mi‐Yoon Chang, Chang‐Hwan Park, Snag‐Mi Kim, Jae‐Jin Song, Sang‐Min Oh, Sang‐Hoon Yi, Bo‐Hyun You, Hyoen‐Ho Kim, Jin‐Wu Nam, and Sang‐Hun Lee, Lin28a enhances the therapeutical potential of cultured neural stem cells in a Parkinson¡¯s disease model. Brain, 139(Pt 10):2722‐2739, 2016. Jin‐Wu Nam, Seo‐Won Choi, and Bo‐Hyun You, Incredible RNA: Dual Functions of Coding and Noncoding. Mol. Cells. 39(5):367‐374. 2016. Kyoungwoo Nam, Heesu Jeong, and Jin‐Wu Nam. Pseudo‐Reference‐Based Assembly of Vertebrate Transcriptomes. Genes, 7:10, 2016. Jiwon Shim and Jin‐Wu Nam. The expression and functional roles of microRNAs in stem cell differentiation. BMB reports, 49(1): 3‐10, 2016. Hoin Kang, Chongtae Kim, Heejin Lee, Jun Gi Rho, Jwa‐Won Seo, Jin‐Wu Nam, Woo Keun Song, Sukoo Nam, Wook Kim and Eun Kyung Lee, Downregulation of microRNA‐362‐3p and microRNA‐329 promotes tumor progression in human breast cancer. Cell Death & Diff., 23(3):484‐95. 2016. Vikram Agarwal, George W. Bell, Jin‐Wu Nam, David P.Bartel, Predicting effective microRNA target sites in mammalian mRNAs. eLife, 4:e05005. 2015. (Citation number: 118). MinHyeok Kim, Bo‐Hyun You, and Jin‐Wu Nam. Global Estimation of the 3' Untranslated Region Landscape Using RNA Sequencing. Methods, 83:111‐117, 2015. (Citation number: 2). J.‐W. Nam, O. Rissland, D. Kopstein, V. Agarwal, C. Jan, M. Yildrim and D. Bartel, Global analyses of the effect of different cellular contexts on microRNA targeting. , Mol Cell, 53(6), 1031–1043, 2014. (Citation number: 55). June Hyun Park, Soungyub Ahn, Soyoung Kim, Junho Lee, Jin‐Wu Nam*, Chanseok Shin* Degradome sequencing reveals an endogenous microRNA target in C. elegans, FEBS Letters 587(2013) 964‐969, 2013. (Citation number: 6). J.‐W. Nam and D. Bartel, Long non‐coding RNAs in C.elegans. Genome Research. 22: 2529‐2540, 2012. Media: Nature Method. (Citation number: 91). C.Shin*, J.‐W. Nam*, K.Farh*, R.Chiang, A.Shkumatava, and D.Bartel. Expanding the MicroRNA Targeting Code: A Novel Type of Site with Centered Pairing., Mol Cell, 38(6):789‐802, 2010. Highlight paper (Citation number: 365). S. Hyun*, J.H. Lee*, H. J*. J.‐W. Nam, B.J. Namkoong, G. Lee, J. Chung, V.N. Kim, Conserved MicroRNA miR‐8/miR‐200 and Its Target USH/FOG2 Control Growth by Regulating PI3K, Cell, 139(6):1096‐1108, 2009. (Citation number: 92). S. Y. Park*, J. H. Lee*, M. Ha, J.‐W. Nam and V. N. Kim. "miR‐29 miRNAs activate p53 by targeting p85a and CDC42" Nature Structural and Molecular Biology 16(1):23‐9, 2009 (Citation number: 472). J.‐W. Nam, I.‐H. Lee, K.‐B. Hwang, S.‐B. Park, and B.‐T. Zhang, Dinucleotide step parameterization of remiRNAs using multi‐objective evolutionary algorithms. EvoBio, 2007. M. Oh, H. Lee, Y.‐K. Kim, J.‐W. Nam, J.‐K. Rhee, B.‐T. Zhang, V.N. Kim, I. Lee, Identification and characterization of small RNAs from vernalized Arabidopsis thaliana, Journal of Plant Biology, 50(5):562‐572, 2007 (Citation number: 4). J.‐G. Joung, K.‐B.Hwang, J.‐W. Nam, S.‐J. Kim, B.‐T. Zhang. Discovery of microRNA‐mRNA modules via population‐based probabilistic learning. Bioinformatics 23:1141‐1147, 2007. (Citation number: 116). J. Han, Y.T. Kim, K.‐H Yeom, J.‐W. Nam, I.H. Hur, Je‐keun Rhee, B.‐T. Zhang and V.N. Kim. Molecular basis for the recognition and processing of primary microRNA by Drosha. Cell, 125:887‐901, 2006. (Citation number: 1215). J.‐W. Nam*, J.H.Kim*, S.K.Kim, B.‐T. Zhang. ProMiR II: a web server for the probabilistic prediction of clustered, nonclustered, conserved and nonconserved microRNAs. Nucleic Acids Research 34:W455‐W458, 2006 (Citation number: 75). J.‐W. Nam*, S.K. Kim* Je‐Keun Rhee, W.J. Lee, B.‐T. Zhang. miTarget: microRNA target‐gene prediction using a Support Vector Machine. BMC Bioinformatics 7(1):411, 2006. Highlight paper (Citation number:209). V.N. Kim and J.‐W. Nam, Genomics of microRNA. Trends in Genetics, 22(3):165‐173, 2006. Most downloaded paper (Citation number: 819). SA Lee, KM Lee, WY Park, B Kim, J.‐W. Nam, KY Yoo, DY Noh, SH Ahn, A Hironen, D Kang. Obesity and genetic polymorphism of ERCC2 and ERCC2 as modifiers of risk of breast cancer. Exp. Mol. Med. 37(2):86‐90, 2005. (Citation number: 39). J.‐W. Nam,
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