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Publications
- 2024
[i12]Yinhua Piao, Sangseon Lee, Yijingxiu Lu, Sun Kim:
Improving out-of-distribution generalization in graphs via hierarchical semantic environments. CoRR abs/2403.01773 (2024)- 2023
- [j97]Minwoo Pak
, Sangseon Lee, Inyoung Sung, Bonil Koo, Sun Kim:
Improved drug response prediction by drug target data integration via network-based profiling. Briefings Bioinform. 24(2) (2023) - [j96]Jeonghyeon Gu, Dongmin Bang, Jungseob Yi, Sangseon Lee, Dong Kyu Kim, Sun Kim:
A model-agnostic framework to enhance knowledge graph-based drug combination prediction with drug-drug interaction data and supervised contrastive learning. Briefings Bioinform. 24(5) (2023) - 2022
- [j93]Inyoung Sung, Sangseon Lee, Minwoo Pak, Yunyol Shin, Sun Kim:
AutoCoV: tracking the early spread of COVID-19 in terms of the spatial and temporal patterns from embedding space by K-mer based deep learning. BMC Bioinform. 23-S(3): 149 (2022) - [j91]Ji Hwan Moon, Sangseon Lee, Minwoo Pak, Benjamin Hur, Sun Kim:
MLDEG: A Machine Learning Approach to Identify Differentially Expressed Genes Using Network Property and Network Propagation. IEEE ACM Trans. Comput. Biol. Bioinform. 19(4): 2356-2364 (2022) - [c63]Yinhua Piao, Sangseon Lee, Dohoon Lee, Sun Kim:
Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification. AAAI 2022: 11165-11173 - [c62]Jungwoo Kim, Sangsoo Lim, Sangseon Lee, Changyun Cho, Sun Kim:
Embedding of FDA Approved Drugs in Chemical Space Using Cascade Autoencoder with Metric Learning. BigComp 2022: 363-365 - [i9]Sangseon Lee, Dohoon Lee, Yinhua Piao, Sun Kim:
SPGP: Structure Prototype Guided Graph Pooling. CoRR abs/2209.07817 (2022) - 2021
- [j84]Sangseon Lee, Taeheon Lee, Yung-Kyun Noh, Sun Kim:
Ranked k-Spectrum Kernel for Comparative and Evolutionary Comparison of Exons, Introns, and CpG Islands. IEEE ACM Trans. Comput. Biol. Bioinform. 18(3): 1174-1183 (2021) - [c60]Inyoung Kim, Sangseon Lee, Youngkuk Kim, Hugh Namkoong, Sun Kim:
A probabilistic model for pathway-guided gene set selection. BIBM 2021: 2733-2740 - [i7]Yinhua Piao, Sangseon Lee, Dohoon Lee, Sun Kim:
Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification. CoRR abs/2112.06386 (2021) - 2020
- [j83]Sangsoo Lim, Sangseon Lee, Inuk Jung, SungMin Rhee, Sun Kim:
Comprehensive and critical evaluation of individualized pathway activity measurement tools on pan-cancer data. Briefings Bioinform. 21(1): 36-46 (2020) - [j82]Sangseon Lee, Sangsoo Lim, Taeheon Lee, Inyoung Sung, Sun Kim:
Cancer subtype classification and modeling by pathway attention and propagation. Bioinform. 36(12): 3818-3824 (2020) - 2019
- [j76]Do-Hoon Lee, Sangseon Lee, Sun Kim:
PRISM: methylation pattern-based, reference-free inference of subclonal makeup. Bioinform. 35(14): i520-i529 (2019) - [j73]Benjamin Hur, Dongwon Kang, Sangseon Lee, Ji Hwan Moon, Gung Lee, Sun Kim:
Venn-diaNet : venn diagram based network propagation analysis framework for comparing multiple biological experiments. BMC Bioinform. 20-S(23): 667 (2019) - 2018
- [c53]Dongwon Kang, Hongryul Ahn, Sangseon Lee, Chai-Jin Lee, Jihye Hur, Woosuk Jung, Sun Kim:
Identifying stress-related genes and predicting stress types in Arabidopsis using logical correlation layer and CMCL loss through time-series data. BIBM 2018: 399-404 - 2017
- [j60]Ji Hwan Moon, Sangsoo Lim, Kyuri Jo, Sangseon Lee, Seokjun Seo, Sun Kim:
PINTnet: construction of condition-specific pathway interaction network by computing shortest paths on weighted PPI. BMC Syst. Biol. 11(S-2): 15:1-15:13 (2017) - [c50]Sangseon Lee, Ji Hwan Moon, Youngjune Park, Sun Kim:
Flow maximization analysis of cell cycle pathway activation status in breast cancer subtypes. BigComp 2017: 91-95 - 2016
- [j50]Heejoon Chae, Sangseon Lee, Kenneth P. Nephew, Sun Kim:
Subtype-specific CpG island shore methylation and mutation patterns in 30 breast cancer cell lines. BMC Syst. Biol. 10(4): 433-443 (2016)
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