Jo K, Sung I, Lee D, Jang H, Kim S. Inferring transcriptomic cell states and transitions only from time series transcriptome data. Scientific Reports, 2021 Jun 15; 11:12566.
Kim S*, Bae S*, Piao Y, Jo K. Graph Convolutional Network for Drug Response Prediction Using Gene Expression Data. Mathematics, 2021 Apr 2; 9(7):772.
Oh M, Park S, Lee S, Lee D, Lim S, Jeong D, Jo K, Jung I, Kim S. DRIM: A web-based system for investigating drug response at the molecular level by condition-specific multi-omics data integration. Frontiers in Genetics, 2020 Nov 12; 11:1-14.
Buitrago B*, Jo K*, Kim M*, Rhee S, Talcott C, Kim S. Logic-based analysis of gene expression data predicts association between TNF, TGFB1 and EGF pathways in basal-like breast cancer. Methods, 2020 Jul 1; 179:89-100.
Kim HJ, Moon JH, Chung H, Shin JS, Kim B, Kim JM, Kim JS, Yoon IH, Min BH, Kang SJ, Kim YH, Jo K, Choi J, Chae H, Lee WW, Kim S, Park CG. Bioinformatic analysis of peripheral blood RNA-sequencing sensitively detects the cause of late graft loss following overt hyperglycemia in pig-to-nonhuman primate islet xenotransplantation. Scientific Reports, 2019 Dec 11; 9(1):1-11.
Kim JI, Park J, Ji Y, Jo K, Han SM, Sohn JH, Shin KC, Han JS, Jeon YG, Goong HN, Han KH, Kim J, Kim S, Choe SS, Kim JB. During adipocyte remodeling, lipid droplet configurations regulate insulin sensitivity through F-actin and G-actin reorganization. Molecular and Cellular Biology, 2019 Sep 27; 39(20):e00210-19.
Ahn H*, Jo K*, Jeong D, Pak M, Hur J, Jung W, Kim S. PropaNet: Time-varying condition-specific transcriptional network construction by network propagation. Frontiers in Plant Science, 2019 June 14; 10: 698.
Hwang I, Jo K, Shin KC, Kim JI, Ji Y, Park YJ, Park J, Jeon YG, Ka S, Suk S, Noh HL, Choe SS, Alfadda AA, Kim JK, Kim S, Kim JB. GABA-stimulated adipose-derived stem cells suppress subcutaneous adipose inflammation in obesity. Proceedings of the National Academy of Sciences of the United States of America, 2019 June 11; 116(24):11936-11945.
Kang H*, Ahn H*, Jo K, Oh M, Kim S. mirTime: Identifying Condition-Specific Targets of MicroRNA in Time-series Transcript Data using Gaussian Process Model and Spherical Vector Clustering. Bioinformatics, 2019 May 9 (online).
Jung I, Jo K, Kang H, Ahn H, Yu Y, Kim S. TimesVector: A vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes. Bioinformatics, 2017 Dec 1;33(23):3827-3835.
Moon JH, Lim S, Jo K, Lee S, Seo S, Kim S. PINTnet: construction of condition-specic pathway interaction network by computing shortest paths on weighted PPI. BMC Systems Biology, 2017 Mar 14; 11(Suppl 2): 15.
Lee J, Jo K, Lee S, Kang J, Kim S. Prioritizing biological pathways by recognizing context in time-series gene expression data. BMC Bioinformatics, 2016 Dec 23;17(17):477.
Jo K, Jung I, Moon JH, Kim S. Influence maximization in time bounded network identifies transcription factors regulating perturbed pathways. Bioinformatics, 2016 Jun 15;32(12):i128-i136.
Jo K, Kwon HB, Kim S. Time-series RNA-seq analysis package (TRAP) and its application to the analysis of rice, Oryza sativa L. ssp. Japonica, upon drought stress. Methods, 2014 Jun 1;67(3):364-72.
*: Equal contributors
Jo K, Jung I, Moon JH, Kim S. Influence maximization in time bounded network identifies transcription factors regulating perturbed pathways. Intelligent Systems for Molecular Biology (ISMB) 2016, Jul 8-12, Orlando, FL.
Kim HJ, Moon JH, Shin JS, Kim JS, Min BH, Kim JM, Kim YH, Lee WW, Kang BC, Kang SJ, Kim SJ, Jo K, Kim S, Park CG. A new bioinformatics analysis reveals intestinal infection as a possible cause of intrahepatic graft rejection in non-human primate porcine islet xenotransplantation. IPITA-IXA-CTS 2015, Nov 15-19, Melbourne, Australia
조겨리, 김선. 네트워크를 이용한 시계열 유전체 분석 기법의 연구 동향. 정보과학회지, Vol.32, No. 10, 2014. 10., pp22-27.
Korean Society for Bioinformatics and Systems Biology BIOINFO 2015, Oct 23.