Sudhir Gopal Tattikpta, Yanhui Hu, Yifang Liu, Bumsik Cho, Vibtor Barrera, Michael Steinbaugh, Sang-Ho Yoon, Aram Comjean, Fangge Li, Franz Dervis, Ruei-Jiun Hung, Jin-Wu Nam, Shannan Ho Sui, Jiwon Shim, Norbert Perrimon. A Single-cell survey of Drosophila blood, elife, 9:e54818, 2020.
HERES-Wnt signaling regulator
Bo-Hyun You*, Jung-Ho Yoon*, Hoin Kang, Eun Kyung Lee, Sang Kil Lee#, and Jin-Wu Nam#. HERES, a IncRNA that Regulates Canonical and Noncanonical Wnt Signaling Pathways via Interaction with EZH2, PNAS, 116(49):24620-24629, 2019.
Genome and Transcriptome Analyses of Jejuma
Krishnamoorthy Srikanth, Nam-Young Kim, Woncheoul Park, Jae-Min Kim, Kwon-Do Kim, Kyung-Tai Lee, Ju-Hwan Son, Han-Ha Chai, Jung-Woo Choi, Gul-Won Jang, Heebal Kim, Youn-Chul Ryu, Jin-Wu Nam, Jong-Eun Park, Jun-Mo Kim & Dajeong Lim. Comprehensive genome and transcriptome analyses reveal genetic relationship, selection signature, and transcriptome landscape of small-sized Korean native Jeju, Scientific Reports, 9(1):16672, 2019.
Assessment of inflammation in Pulmonary Artey Hypertension
Jun-Bean Park, Jae-Hoon Choi, Jin-Wu Nam, Hyung-Kwan Kim, Yun-Sang Lee, Jae Min Jeong, Yong-Jin Kim, Jin Chul Paeng and Seung-Pyo Lee. Assesment of inflammation in pulmonary artery hypertension by 68Ga-Mannosylated Human serum albumin, American journal of Respiratory and Critical Care Medicine, 201(1):95-106, 2020.
UPF1-mediated miRNA targeting
Jeongyoon Park*, Jwa-Won Seo*, Narae Ahn, Seokju Park, Jungwook Hwang#, and Jin-Wu Nam#.UPF1/SMG7-dependent MicroRNA-mediated Gene Regulation, Nature Communications, 10(1):4181, 2019.
Functional Elements of Human XIST
Hyeon Lee*, Rama Gopalappa, Hongjae Sunwoo*, Seowon Choi, Suresh Ramakrishna, Jeannie Lee, Hyongbum (Henry) Kim#, Jin-Wu Nam#. En bloc and segmental deletions of human XIST reveal X chromosome inactivation- involving RNA elements, Nucleic Acids Res, 47(8):3875-3887, 2019.
ARE-mediated mRNA decay
Incheol Ryu, Yeonkyoung Park, Jwa-Won Seo, Ok Hyun Park, Hongseok Ha, Jin-Wu Nam and Yoon Ki Kim. HuR stabilizes a polydenylated form of replication-dependent histone mRNas under stress conditions, FASEB, 33(2):2680-2693, 2019.
The small peptide in LncRNAs
Seo-Won Choi*, Hyunwoo Kim*, and Jin-Wu Nam. The small peptide world in long non-coding RNAs, Briefings in Bioinformatics, 20(5):1853-1864, 2019.
Transcriptome Analysis of Non-Foamy cells in Atherosclerotic Murine Models
Kyeongdae Kim , Dahee Shim , Jun Seong Lee , Konstantin Zaitsev , Jesse W Williams , Ki-Wook Kim , Man-Young Jang , Hyung Seok Jang , Tae Jin Yun , Seung Hyun Lee , Won Kee Yoon , Annik Prat , Nabil G Seidah , Jungsoon Choi , Seung-Pyo Lee , Sang-Ho Yoon , Jin Wu Nam , Je Kyung Seong, Goo Taeg Oh , Gwendalyn Randolph , Maxim N Artyomov , Cheolho Cheong , and Jae-Hoon Choi . Transcriptome Analysis Reveals Non-Foamy Rather than Foamy Plaque Macrophages Are Pro-Inflammatory in Atherosclerotic Murine Models, Circulation Res, 123(10) :1127-1142, 2018.
HSF2 and lncRNAs in black tissues
Hyosun Hong*, Han-Ha Chai*, Kyoungwoo Nam, Dajeong Lim, Kyung-Tai Lee, Yoon Jung Do, Chang-Yeon Cho and Jin-Wu Nam. HSF2 Co-regulates Protein-coding and Long Non-coding RNA Genes Specific to Black Tissues of the Black Chicken, Yeonsan Ogye , International Journal of Molecular Sciences, 19(8):E2359, 2018.
Ogye draft genome and transcriptomes
Jang-il Sohn*, Kyoungwoo Nam*, Hyosun Hong*, Jun-Mo Kim*, Dajeong Lim, Kyung-Tai Lee, Yoon Jung Do, Chang Yeon Cho,Namshin Kim, Han-Ha Chai# and Jin-Wu Nam#. Whole genome and transcriptome maps of the entirely black native Korean chicken breed Yeonsan Ogye , GigaSciences, 7(7):giy086, 2018.
LUCAT1 in ESCC
Jung-Ho Yoon, Bo-Hyun You, Chan Hyuk Park, Yeong Jin Kim, Jin-Wu Nam, and Sang Kil Lee. The long noncoding RNA LUCAT1 promotes tumorigenesis by controlling ubiquitination and stability of DNA methyltransferase 1 in esophageal squamous cell carcinoma, Cancer Letters, 417:47-57, 2018.
Seo-Won Choi and Jin-Wu Nam. TERIUS: accurate prediction of lncRNA via high-throughput sequencing data representingRNA binding protein association, BMC Bioinformatics, 19(1):14, 2018.
De Novo Whole Genome Assembly
Jang-il Sohn and Jin-Wu Nam. The Present and Future of De Novo Whole GenomeAssembly, Briefings in Bioinformatics , 19(1):23-40, 2018.
Dooyoung Lee, Jin-Wu Nam, and Chanseok Shin. DROSHA targets its own transcript to modulate alternative splicing, RNA, 23(7):1035-1047, 2017.
Targeted Exomse Sequencing in TN-Breast Cancer
Hae Min Jeong, Ryong Nam Kim, Mi Jeong Kwon, Ensel Oh, Jinil Han, Se Kyung Lee, Jong-Sun Choi, Sara Park, Seok Jin Nam, Gyung Yup Gong, Jin Wu Nam, Doo Ho Choi, Hannah Lee, Byung-Ho Nam, Yoon-La Choi and Young Kee Shin. Targeted exome sequencing of Korean triple-negative breast cancer reveals homozygous deletions associated with poor prognosis of adjuvant chemotherapy-treated patients, Oncotarget, 8(37):61538-61550, 2017.
Co-assembly of Transcriptome
Bo-Hyun You, Sang-Ho Yoon, and Jin-Wu Nam. High-Confidence Coding and Noncoding Transcriptome Maps, Genome Res, 27(6):1050-1062, 2017.
miRNA-mediated silencing of mRNA-like lncRNAs
Kyung-Tae Lee and Jin-Wu Nam. Post-transcriptional and translational regulation of mRNA-like long non-coding RNAs by microRNAs in early developmental stages of zebrafish embryos, BMB Rep, 50(4):226-231, 2017.
Endogenous Cpf1 efficiency predictor
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, 14(2):153-159, 2017.
Network-based Tumour Purity
Youngjune Park, Sangsoo Lim, Jin-Wu Nam, and Sun Kim. Measuring intratumor heterogeneity by network entropy using RNA-seq data, Sci. Rep, 6:37767, 2016.
Parkinson’s disease therapy by NSCs expanded with LIN28A
Yong-Hee Rhee, Tae-Ho Kim, A-Young Jo, Mi-Yoon Chang, Chang-Hwan Park,Sang-Mi Kim, Jae-Jin Song, Sang-Min Oh, Sang-Hoon Yi, Hyeon Ho Kim, Bo-Hyun You, Jin-Wu Nam, and Sang-Hun Lee. LIN28A enhances the therapeutic potential of cultured neural stem cells in a Parkinson’s disease model, Brain, 139(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.
Pseudo-Reference-Based Assembly of Vertebrate Transcriptomes
Jiwon Shim, Jin-Wu Nam. The expression and functional roles of microRNAs in stem cell differentiation, BMB Reports, 49(1):3-10, 2016.
micoRNA-362-3p/329 as tumor suppressor
Hoin Kang, Chongtae Kim, Heejin Lee, Jun Gi Rho, Jwa-Won Seo, Jin-Wu Nam, Woo Keun Song, Suk Woo 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):484-495, 2016.
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.
Vikram Agarwal, George W. Bell, Jin-Wu Nam, David P.Bartel. Predicting effective microRNA target sites in mammalian mRNAs, eLife, 4:e05005, 2015.
Cell-type specific miRNA targeting
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.
miRNA-mediated cleavage target
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.
lncRNAs in C. elegans
J.-W. Nam and D. Bartel. Long non-codingRNAs in C.elegans, Genome Research, 22:2529-2540, 2012.
Centered sites of miRNAs
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.
The common miR-8/miR-200 targeting
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.
B.-T Zhang and J.-W. Nam. Supervisedlearning approach for microRNA studies, Machine Learning in Bioinformatics, Chapter 16, John Wiley & Sons, 2008.
miR-29 and cancer
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):23-29, 2008.
J.H. Namkung, J.-W. Nam, and TS Park. Identification of eQTL by the interaction analysis using genetic algorithm, BMC proc.
The tertiary structure of pre-miRNA
J.-W. Nam, I.-H. Lee, K.-B. Hwang, S.-B. Park, and B.-T. Zhang. Dinucleotide step parameterization of pre-miRNAs using multi-objective evolutionary algorithms, EvoBio, 4447:176-186, 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.
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.
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.
PromiRII: miRNA prediction
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.
miTarget: miRNA target prediction
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.
Review: genomics of miRNA
V.N. Kim and J.-W. Nam. Genomics of microRNA, Trends in Genetics, 22(3):165-173, 2006.
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, 2006.
ProMiR: miRNA prediction
J.-W. Nam, K.R. Shin, J.J. Han, Y.T. Lee, V.N. Kimand B.T.Zhang. Human miRNA prediction through probabilistic co-learning of sequence and structure, Nucleic Acids Research, 33(11):3570-3581, 2005.
S.K. Kim, J.-W. Nam, W.J. Lee, B.T. Zhang. A Kernel Method for MicroRNA Target Prediction Using Sensible Data and Position-Based Features. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB 2005), pp. 46-52, 2005.
C. elegans miRNA targets
W.J. Lee, J.-W. Nam, S.K. Kim, B.T. Zhang. Identification of C.elegans MicroRNA Targets Using a Kernel Method, Genomics and Informatics, 3(1):15-23, 2005.
miRNA precursor prediction
J.-W. Nam, W.J. Lee, B.T. ZHANG. Computational Methods for Identification of Human microRNA Precursors, Lecture Notes in Artificial Intelligence, vol 3157, 2005.
E.-J. Park, J.-W. Nam, I.-H. Lee, and B.-T. Zhang Solving the monkey and banana problem using DNA computing. Preliminary Proceedings of the Tenth International Meeting on DNA Computing (DNA10), p.452, 2004.
J.-W. Nam, Joung, J.-G., Ahn, Y.S. and Zhang, B.-T. Two-Step Genetic Programming for Optimization of RNA Common-Structure, Lecture Notes in Computer Science, vol 3005, 73-83, 2004.