| Transcriptional network analysis reveals drought resistance specific biological mechanisms underlying AP2/ERF transgenic rice species H Ahn, I Jung, SJ Shin, J Park, S Rhee, JK Kim, W Jung, HB Kwon, S Kim Frontiers in Plant Science 8, 1044, 2017 | 56* | 2017 |
| A multifunctional protein EWS regulates the expression of Drosha and microRNAs KY Kim, YJ Hwang, MK Jung, J Choe, Y Kim, S Kim, CJ Lee, H Ahn, J Lee, ... Cell Death and Differentiation 21 (1), 136, 2014 | 48 | 2014 |
| TimesVector: a vectorized clustering approach to the analysis of time series transcriptome data from multiple phenotypes I Jung, K Jo, H Kang, H Ahn, Y Yu, S Kim Bioinformatics 33 (23), 3827-3835, 2017 | 39 | 2017 |
| Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer CJ Lee, H Ahn, D Jeong, M Pak, JH Moon, S Kim BMC Medical Genomics 13 (3), 27, 2020 | 33 | 2020 |
| Functional in vivo and in vitro effects of 20q11. 21 genetic aberrations on hPSC differentiation HY Jo, Y Lee, H Ahn, HJ Han, A Kwon, BY Kim, HY Ha, SC Kim, JH Kim, ... Scientific reports 10 (1), 18582, 2020 | 28 | 2020 |
| Identification of conserved gene-regulatory networks that integrate environmental sensing and growth in the root cambium NV Hoang, G Choe, Y Zheng, ACA Fandino, I Sung, J Hur, M Kamran, ... Current Biology 30 (15), 2887-2900. e7, 2020 | 27 | 2020 |
| Clustering and evolutionary analysis of small RNAs identify regulatory siRNA clusters induced under drought stress in rice I Jung, H Ahn, SJ Shin, J Kim, HB Kwon, W Jung, S Kim BMC Systems Biology 10 (4), 115, 2016 | 13 | 2016 |
| PropaNet: Time-varying condition-specific transcriptional network construction by network propagation H Ahn, K Jo, D Jung, M Park, J Hur, W Jung, S Kim Frontiers in Plant Science 10, 698, 2019 | 11 | 2019 |
| Network Propagation for the Analysis of Multi-omics Data M Pak, D Jeong, JH Moon, H Ann, B Hur, S Lee, S Kim Recent Advances in Biological Network Analysis, 185-217, 2021 | 10 | 2021 |
| mirTime: identifying condition-specific targets of microRNA in time-series transcript data using Gaussian process model and spherical vector clustering H Kang, H Ahn, K Jo, M Oh, S Kim Bioinformatics 37 (11), 1544-1553, 2021 | 9 | 2021 |
| Integration of heterogeneous time series gene expression data by clustering on time dimension H Ahn, H Chae, W Jung, S Kim 2017 IEEE International Conference on Big Data and Smart Computing (BigComp …, 2017 | 8 | 2017 |
| Novel drought-responsive regulatory coding and non-coding transcripts from Oryza Sativa L. SJ Shin, H Ahn, I Jung, S Rhee, S Kim, HB Kwon Genes & Genomics 38, 949-960, 2016 | 8 | 2016 |
| HTRgene: a computational method to perform the integrated analysis of multiple heterogeneous time-series data: case analysis of cold and heat stress response signaling genes in … H Ahn, I Jung, H Chae, D Kang, W Jung, S Kim BMC bioinformatics 20 (16), 1-14, 2019 | 7 | 2019 |
| Integrated analysis of omics data using microRNA-target mRNA network and PPI network reveals regulation of Gnai1 function in the spinal cord of Ews/Ewsr1 KO mice CJ Lee, H Ahn, SB Lee, JY Shin, WY Park, JI Kim, J Lee, H Ryu, S Kim BMC Medical Genomics 9 (1), 33, 2016 | 6 | 2016 |
| Formulation of a problem for the integrated analysis of heterogeneous time-series gene expression data and cold stress response gene set analysis in Arabidopsis D Kang, H Ahn, W Jung, S Kim Proc Korean Inf Sci Soc Confer, 648-50, 2015 | 6 | 2015 |
| Identifying stress-related genes and predicting stress types in Arabidopsis using logical correlation layer and CMCL loss through time-series data D Kang, H Ahn, S Lee, CJ Lee, J Hur, W Jung, S Kim 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018 | 5 | 2018 |
| StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in arabidopsis D Kang, H Ahn, S Lee, CJ Lee, J Hur, W Jung, S Kim BMC genomics 20 (11), 1-13, 2019 | 3 | 2019 |
| HTRgene: integrating multiple heterogeneous time-series data to investigate cold and heat stress response signaling genes in Arabidopsis H Ahn, I Jung, H Chae, D Kang, W Jung, S Kim 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018 | 3 | 2018 |
| DeepFunNet: deep learning for gene functional similarity network construction H Ahn, S Son, S Kim 2019 IEEE International Conference on Big Data and Smart Computing (BigComp …, 2019 | 2 | 2019 |
| Ensemble Learning to Identify Depression Indicators for Korean Farmers J Park, H Ahn, K Youn, M Lee, S Hong IEEE Access 11, 118787-118800, 2023 | 1 | 2023 |
Sun KimProfessor, Seoul National University; CTO, AIGENDRUG Co. Ltd.Verified email at snu.ac.kr
