In review
  • GraphT5: Unified Molecular Graph-Language Modeling via Multi-Modal Cross-Token Attention.
  • Context-Aware Hierarchical Fusion for Drug Relational Learning.
  • MSA-VF Predictor: Coevolutionary Signals in Protein Sequences for Virulence Factor Prediction using MSA Transformer.
  • An ensemble strategy to improve generalization power of deep learning models for DTI prediction.
  • DrugPT-Net: Drug Perturbation Guided Visible Neural Network for Drug Response Prediction at Transcriptomic Level.
  • MDTR: A Knowledge-Guided Interpretable Representation for Quantifying Liver Toxicity at Transcriptomic Level.
  • ChemAP: Chemical Structure-Based Deep Learning Model via Knowledge Distillation for Predicting Drug Approval before Clinical Trial Phase.
  • Multi-Task Informed Learnable Prototypes on Few Shot learning for Molecular Property Prediction.
  • PULSAR: In silico prioritizing system for phenotype-related genes from mouse KO event using PU learning on biological network.
  • Transcriptome Transformer: Prediction of Clinical Features and Survival from Transcriptome by Modeling Gene Interactions with Transformer in a Multi-task Framework.
  • Residue-Level Multi-View Deep Learning for Accurate ATP Binding Site Prediction and Its Applications in Kinase Drug Binding.
  • Lee S, Park J, Piao Y, Lee D, Lee D, Kim S. Multi-layered Knowledge Graph Neural Network Reveals Pathway-level Agreement of Three Breast Cancer Multi-gene Assays. Computational and Structural Biotechnology Journal. 2024 Apr 22.
  • Koh J, Jeong D, Park SY, Han D, Kim DS, Kim HY, Kim H, Yang S, Kim S, Ryu HS. Identification of VWA5A as a novel biomarker for inhibiting metastasis in breast cancer by machine-learning based protein prioritization. Scientific Reports. 2024 Jan 30.
  • Park S, Lee S, Pak M, Kim S. Dual Representation Learning for Predicting Drug-side Effect Frequency using Protein Target Information. IEEE Journal of Biomedical and Health Informatics. 2024 Jan 5.
Conference proceedings
  • Bang D, Koo B, Kim S. Transfer Learning of Condition-Specific Perturbation in Gene Interactions Improves Drug Response Prediction. [From The 32nd Intelligent Systems for Molecular Biology (ISMB)]
  • Piao Y, Lee S, Lu Y, Kim S. Improving Out-of-Distribution Generalization in Graphs via Hierarchical Semantic Environments. CVPR 2024. 2024 Mar
  • Lee D, Lee D, Bang D, Kim S. DiSCO: Diffusion Schrödinger Bridge for Molecular Conformer Optimization. AAAI 2024. 2024
  • Lu Y, Piao Y, Kim S. Enhancing Drug-Drug Interaction Prediction with Context-Aware Architecture. ICLR 2024 Tiny Paper Track. 2024 Feb 16
  • Jeong D, Koo B, Oh M, Kim TB, Kim S. GOAT: Gene-level biomarker discovery from multi-Omics data using graph ATtention neural network for eosinophilic asthma subtype. Bioinformatics. 2023 Sep 22.
  • Yi J, Lee S, Lim S, Cho C, Piao Y, Yeo M, Kim D, Kim S, Lee S. Exploring chemical space for lead identification by propagating on chemical similarity network. Computational and Structural Biotechnology Journal. 2023 Aug 25.
  • Gu J, Bang D, Yi J, Lee S, Kim DK, Kim S. A model-agnostic framework to enhance knowledge graph-based drug combination prediction with drug–drug interaction data and supervised contrastive learning. Briefings in Bioinformatics. 2023 Aug 7.
  • Jeon H, Ahn J, Na B, Hong S, Lee S, Kim S, Yoon S, Baek D. AIVariant: a deep learning-based somatic variant detector for highly contaminated tumor samples. Experimental & Molecular Medicine. 2023 Aug 1.
  • Yoon JK, Park S, Lee KH, Jeong D, Woo J, Park J, Yi SM, Han D, Yoo CG, Kim S, Lee CH. Machine Learning-Based Proteomics Reveals Ferroptosis in COPD Patient-Derived Airway Epithelial Cells Upon Smoking Exposure. Journal of Korean Medical Science. 2023 July 24.
  • Bang D, Lim S, Lee S, Kim S. Biomedical knowledge graph learning for drug repurposing by extending guilt-by-association to multiple layers. Nature Communications. 2023 June 15.
  • AM Rafi, D Penzar, D Nogina, D Lee, ED Vaishnav, D Lee, N Kim, S Kim, G Meshcheryakov, A Lando, P Yadollahpour, A Zinkevich, D Kim, Y Shin, IY Kwak, BC Kim, J Lee, Random Promoter DREAM Challenge Consortium, S Kim, A Regev, J Albrecht, W Gong, IV Kulakovskiy, P Meyer & CG de Boer. Evaluation and optimization of sequence-based gene regulatory deep learning models. bioRxiv. 2023 Apr 28.
  • C Cho, D Lee, D Jeong, S Kim, MK Kim & S Srinivasan. Characterization of radiation-resistance mechanism in Spirosoma montaniterrae DY10T in terms of transcriptional regulatory system. Scientific Reports 13.1 (2023): 4739. 2023 Mar 23.
  • Lee D, Koo B, Yang J, Kim S. Metheor: Ultrafast DNA methylation heterogeneity calculation from bisulfite read alignments. PLOS Computational Biology. 2023 Mar 20.
  • Lee D, Koo B, Kim S, Byun J, Hong J, Shin D, Sun C, Song J, Kim J, Jaiswal S, Yoon S, Kim S, Koh Y. AMLs harboring DNMT3A-destabilizing variants show increased intratumor DNA methylation heterogeneity at bivalent chromatin domains. bioRxiv. 2023 Feb 14.
  • Pak M, Lee S, Sung I, Koo B, Kim S. Improved drug response prediction by drug target data integration via network-based profiling. Briefings in Bioinformatics. 2023 Feb 8.
  • Lim S, Kim Y, Gu J, Lee S, Shin W, Kim S. Supervised chemical graph mining improves drug-induced liver injury prediction. iScience. 2023 Jan 20.
Conference proceedings
  • Kim NY, Piao Y, Kim S. Clinical Note Owns its Hierarchy: Multi-Level Hypergraph Neural Networks for Patient-Level Representation Learning. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, 2023 July 9.
  • Yang J, Lee D, Koo B, Jeong D, Kim S. Deep learning-based survival prediction using DNA methylation-derived 3D genomic information. 14th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB 2023). 2023 Nov 5.
  • Kwon Y, Lee D, Kim JW, Choi YS, Kim S. Exploring Optimal Reaction Conditions Guided by Graph Neural Networks and Bayesian Optimization. ACS Omega. 2022 Dec 2.
  • Kwon Y, Kim S, Choi YS, Kang S. Generative Modeling to Predict Multiple Suitable Conditions for Chemical Reactions. Journal of Chemical Information and Modeling (JCIM). 2022 Nov 22.
  • Shin J, Piao Y, Bang D, Kim S, Jo K. DRPreter: Interpretable Anticancer Drug Response Prediction Using Knowledge-Guided Graph Neural Networks and Transformer. International Journal of Molecular Sciences (IJMS). 2022 Nov 11.
  • Lee D, Yang J, Kim S. Learning the histone codes with large genomic windows and three-dimensional chromatin interactions using transformer. Nature Communications. 2022 Nov 5.
  • Choi B, Kang CK, Park S, Lee D, Lee AJ, Ko Y, Kang SJ, Kang K, Koh Y, Jung I. Single-cell transcriptome analyses reveal distinct gene expression signatures of severe COVID-19 in the presence of clonal hematopoiesis. Experimental & Molecular Medicine (EMM). 2022 Oct 13.
  • Bang D, Gu J, Park J, Jeong D, Koo B, Yi J, Shin J, Jung I, Kim S, Lee S. A Survey on Computational Methods for Investigation on ncRNA-Disease Association through the Mode of Action Perspective. International Journal of Molecular Sciences (IJMS). 2022 Sep 29.
  • Lim S, Lee S, Piao Y, Choi MG, Bang D, Gu J, Kim S. On Modeling and Utilizing Chemical Compound Information with Deep Learning Technologies: A Task-oriented Approach. Computational and Structural Biotechnology Journal (CSBJ). 2022 Aug 4.
  • Park J, Lee D, Ham S, Oh J, Noh JR, Lee YK, Park YJ, Lee G, Han SM, Han JS, Kim YY, Jeon YG, Nahmgoong H, Shin KC, Kim SM, Choi SH, Lee CH, Park J, Roh TY, Kim S, Kim JB. Targeted erasure of DNA methylation by TET3 drives adipogenic reprogramming and differentiation. Nature Metabolism. 2022 July 4.
  • Kim YY, Jang H, Lee G, Jeon YG, Sohn JH, Han JS, Lee WT, Park J, Huh JY, Nahmgoong H, Han SM, Kim J, Pak M, Kim S, Kim JS, Kim JB. Hepatic GSK3β-Dependent CRY1 Degradation Contributes to Diabetic Hyperglycemia. Diabetes. 2022 July 1.
  • Han JS, Jeon YG, Oh M, Lee G, Nahmgoong H, Han SM, Kim YY, Shin KC, Kim J, Jo K, Choe SS, Park EJ, Kim S, Kim JB. Adipocyte HIF2α functions as a thermostat via PKA Cα regulation in beige adipocytes. Nat Commun., 2022 June .
  • Lee G, Kim Y, Jang H, Han JS, Nahn N, Park YJ, Han SM, Cho C, Lim S, Noh JR, Oh WK, Lee CH, Kim S, Kim JB. SREBP1c-PARP1 axis tunes anti-senescence activity of adipocytes and ameliorates metabolic imbalance in obesity. Cell Metabolism. 2022 May 3.
  • Sung I, Lee S, Pak M, Shin Y, Kim S. 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 Bioinformatics. 2022 Apr 25.
  • Pak M, Lee S, Sung I, Shin Y, Jung I, Kim S. COVID-19 Virus Whole-genome Embedding Strategy through Density-based Clustering and Deep Learning Model. JOK. 2022 Apr.
Conference proceedings
  • Lee S, Lee D, Piao Y, Kim S. SPGP: Structure Prototype Guided Graph Pooling. NeurIPS 2022 New Frontiers in Graph Learning Workshop (NeurIPS GLFrontiers 2022), 2022 Dec 2.
  • Koo B, Lee D, Lee S, Sung I, Kim S, Lee S. Risk Stratification for Breast Cancer Patient by Simultaneous Learning of Molecular Subtype and Survival Outcome Using Genetic Algorithm-Based Gene Set Selection. Cancers. [From The 10th International Conference on Intelligent Biology and Medicine (ICIBM 2022)]. 2022 Aug 25.
  • Piao Y, Lee S, Lee D, Kim S. Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification. AAAI 2022. 2022 Feb 22.
  • Kim J, Lim S, Lee S, Cho C, Kim S. Embedding of FDA Approved Drugs in Chemical Space Using Cascade Autoencoder with Metric Learning. IEEE BigComp 2022. AI-BioHealth 2022 workshop. 2022 Jan 17.
  • Kim M, Lee S, Lim S, Lee DY, Kim S. Subnetwork Representation Learning for Discovering Network Biomarkers in Predicting Lymph Node Metastasis in Early Oral Cancer. Scientific Reports 11 (23992), 1-12. 2021 Dec 14.
  • Lee D, Kim S. Knowledge-guided artificial intelligence technologies for decoding complex multiomics interactions in cells. Clinical and Experimental Pediatrics. 2021 Nov 26. Online ahead of print.
  • Sohn JH, Ji Y, Cho CY, Nahmgoong H, Lim S, Jeon YG, Han SM, Han JS, Park I, Rhee HW, Kim S, Kim JB. Spatial Regulation of Reactive Oxygen Species via G6PD in Brown Adipocytes Supports Thermogenic Function. Diabetes. 2021 Sep 14.
  • Jung I, Kim M, Rhee S, Lim S, Kim S. MONTI: A Multi-Omics Non-negative Tensor Decomposition Framework for Gene-Level Integrative Analysis. Frontiers in Genetics, 2021 Sep 10.
  • Park S, Lee D, Kim Y, Lim S, Chae H, Kim S. BioVLAB-Cancer-Pharmacogenomics: Tumor Heterogeneity and Pharmacogenomics Analysis of Multi-omics Data from Tumor on the Cloud. Bioinformatics. 2021 June 29.
  • Jo K, Sung I, Lee D, Jang H, Kim S. Inferring transcriptomic cell states and transitions only from time series transcriptome data. Scientific Reports 11 (1), 1-13. 2021 June 15.
  • Lee T, Lee S, Kang M, Kim S. Deep hierarchical embedding for simultaneous modeling of GPCR proteins in a unified metric space. Scientific Reports 11 (1) 1-11. 2021 May 05.
  • Jeong D, Lim S, Lee S, Oh M, Cho C, Seong H, Jung W, Kim S. Construction of Condition-Specific Gene Regulatory Network using Kernel Canonical Correlation Analysis. Frontiers in Genetics. 2021 Mar 26.
  • Moon JH, Lee S, Pak M, Hur B, Kim S. MLDEG: A Machine Learning Approach to Identify Differentially Expressed Genes Using Network Property and Network Propagation. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 2021 Mar 22.
  • Park YJ, Lee S, Lim S, Hahn N, Ji Y, Huh JY, Alfadda AA, Kim S, Kim JB. DNMT1 maintains metabolic fitness of adipocytes through acting as an epigenetic safeguard of mitochondrial dynamics. Proceedings of the National Academy of Sciences (PNAS). 2021 Mar 16.
  • Lim S, Lu Y, Cho CY, Sung I, Kim J, Kim Y, Park S, Kim S. A Review on Compound-Protein Interaction Prediction Methods: Data, Format, Representation and Model. Computational and Structural Biotechnology Journal (CSBJ). 2021 Mar 10.
Conference proceedings
  • Kim I, Lee S, Kim Y, Namkoong H, Kim S. A Probabilistic Model for Pathway-guided Gene Set Selection. IEEE BIBM 2021. 12th International Workshop on Biomedical and Health Informatics (BHI 2021). Accepted.
  • Ahn H, Jung I, Chae H, Oh M, Kim I, Kim S. IDEA: Integrating Divisive and Ensemble-Agglomerate hierarchical clustering framework for arbitrary shape data. 2021 IEEE International Conference on Big Data (Big Data). 8th Annual Workshop on Big Data Analytic Technology for Bioinformatics and Health Informatics (KDDBHI), 2021. Accepted.
  • Pak M, Jeong D, Moon JH, Ann H, Hur B, Lee S, Kim S. Network Propagation for the Analysis of Multi-Omics Data. Recent Advances in Biological Network Analysis (pp. 185-217). 2021
  • Lee HB, Lee SB, Kim M, Kwon S, Jo J, Kim J, Lee HJ, Ryu HS, Lee JW, Kim C, Jeong J, Kim H, Noh DY, Park IA, Ahn SH, Kim S, Yoon S, Kim A, Han W. Development and Validation of a Next-Generation Sequencing-Based Multigene Assay to Predict the Prognosis of Estrogen Receptor-Positive, HER2-Negative Breast Cancer. Clinical Cancer Research 26 (24), 6513-6522. 2020 Dec 15.
  • 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.
  • Jo HY, Lee Y, Ahn H, Han HJ, Kwon A, Kim BY, Ha HY, Kim SC, Kim JH, Kim YO, Kim S, Koo SK, Park MH. Functional in vivo and in vitro effects of 20q11.21 genetic aberrations on hPSC differentiation. Scientific reports 10 (1), 1-14. 2020 Oct 29.
  • Min A, Kim K, Jeong K, Choi S, Kim SY, Suh K-J, Lee K-H, Kim S, Im S-A. Homologous Repair Deficiency score for identifying breast cancers with defective DNA damage response beyond BBCA mutations. Scientific Reports, 10(1):1-14, 2020 Jul 27.
  • Kang M, Lee S, Lee D, Kim S. Learning Cell-Type-Specific Gene Regulation Mechanisms by Multi-Attention Based Deep Learning with Regulatory Latent Space. Frontiers in Genetics, 2020 Sep 30.
  • Lee D, Park Y, Kim S. Towards multi-omics characterization of tumor heterogeneity: a comprehensive review of statistical and machine learning approaches. Briefings in Bioinformatics, 2020 Aug 25.
  • Jo K, Santos-Buitrago B, 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 July 1.
  • Hoang N. V., Choe G, Zheng Y, Fandino A. C. A, Sung I, Hur J, Kamran M, Park C, Kim H, Ahn H, Kim S, Fei Z, Lee J. Identification of Conserved Gene-Regulatory Networks that Integrate Environmental Sensing and Growth in the Root Cambium. Current Biology, 2020 Aug 3.
  • Oh M, Park S, Kim S, Chae H. Machine learning-based analysis of multi-omics data on the cloud for investigating gene regulations. Briefings in Bioinformatics, 2020 Mar 30.
  • Lee S, Lim S, Lee T, Sung I, Kim S. Cancer subtype classification and modeling by pathway attention and propagation. Bioinformatics, 2020 Mar 24.
  • Jo HY, Han HW, Jung I, Ju JH, Park SJ, Moon S, Geum D, Kim H, Park HJ, Kim S, Stacey G.N., Koo SK, Park MH. Development of genetic quality tests for good manufacturing practice-compliant induced pluripotent stem cells and their derivatives. Scientific Reports, 2020 Mar 3.
  • Lee CJ, Ahn H, Jeong D, Pak M, Moon JH, Kim S. Impact of mutations in DNA methylation modification genes on genome-wide methylation landscapes and downstream gene activations in pan-cancer. BMC Medical Genomics, 2020 Feb 24. [From The 30th International Conference on Genome Informatics (GIW)]
  • Hur B, Kang D, Lee S, Moon JH, Lee G, Kim S. Venn-diaNet: Venn diagram based network propagation analysis framework for computing multiple biological experiments. BMC Bioinformatics, 2019 Dec 27. [From The 30th International Conference on Genome Informatics (GIW)]
  • Kang D, Ahn H, Lee S, Lee CJ, Hur J, Jung W, Kim S. StressGenePred: a twin prediction model architecture for classifying the stress types of samples and discovering stress-related genes in Arabidopsis. BMC Genomics, 2019 Dec 20.
  • Kim HJ, Moon JH, Shin JS, Kim B, Kim JS, Yoon IH, Min BH, Kim JM, Kang SJ, Kim YH, Jo K, Choi J, Chae H, Lee WW, Kim S, Park CG. Bioinformatics analyses with peripheral blood RNA-sequencing unveiled the cause of the graft loss after pig-to-nonhuman primate islet xenotransplantation model. Scientific Reports. 2019 Dec 11
  • Ahn H, Jung I, Chae H, Kang D, Jung W, Kim S. 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 Arabidopsis. BMC Bioinformatics, 2019 Dec 2.
  • Kim M, Lee S, Lim S, Kim S. SpliceHetero: An information theoretic approach for measuring spliceomic intratumor heterogeneity from bulk tumor RNA-seq. PloS ONE. 2019 Oct 23.
  • Lee S, Lee T, Noh YK, Kim S. Ranked k-spectrum kernel for comparative and evolutionary comparison of exons, introns, and CpG islands. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2019 Sep 3.
  • Lim A, Lim S, Kim S. Enhancer Prediction with Histone Modification Marks Using a Hybrid Neural Network Model. Methods, 2019 Aug 15.
  • 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/G-actin reorganization. Molecular and Cellular Biology, 2019 Jul 20
  • Lee D, Lee S, Kim S. PRISM: Methylation Pattern-based, Reference-free Inference of Subclonal Makeup. Bioinformatics, 2019 Jul 5. [From The 27th Intelligent Systems for Molecular Biology (ISMB)]
  • Jang Y, Seo J, Jang I, Lee B, Kim S, Lee S. CaPSSA: visual evaluation of cancer biomarker genes for patient stratification and survival analysis using mutation and expression data. Bioinformatics, 2019 Jun 22
  • Kim S, Kang JW, Yoon S. Cracking the code of personalized medicine. Nature Research 2019 (advertisement article).
  • 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 Jun 14.
  • 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 (PNAS), 2019 Jun 3.
  • 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.
  • Park S, Kim M, Seo S, Hong S, Han K, Lee K, Cheon JH, Kim S. A secure SNP panel scheme using homomorphically encrypted K-mers without SNP calling on the user side. BMC Genomics, 2019 Apr 4. [From The 17th Asia Pacific Bioinformatics Conference (APBC)]
Conference proceedings
  • Ahn H, Son S, Kim S. DeepFunNet: Deep Learning for Gene Functional Similarity Network Construction. The 6th IEEE International Conference on Big Data and Smart Computing (BigComp), 2019 Mar 2.
  • Choi J, Park Y, Kim S, Chae H. CloudBS: A MapReducebased bisulfite sequencing aligner on cloud. Journal of Bioinformatics and Computational Biology. 2018 Dec 19.
  • Seo S, Park Y, Chae H. BiSpark: a Spark-based highly scalable aligner for bisulfite sequencing data. BMC Bioinformatics. 2018 Dec 10.
  • Lim S, Lee S, Jung I, Rhee S, Kim S. Comprehensive and critical evaluation of individualized pathway activity measurement tools on pan-cancer data. Briefings in Bioinformatics. 2018 Nov 20.
  • Seo S, Oh M, Park Y, Kim S. DeepFam: Deep learning based alignment-free method for protein family modeling and prediction. Bioinformatics, 2018 Jul 1. [From The 26th Intelligent Systems for Molecular Biology (ISMB)]
  • Lee CJ, Kang D, Lee S, Lee S, Kang J, Kim S. In silico experiment system for testing hypothesis on gene functions using three condition specific biological networks. Methods. 2018 May 11.
  • Jung I, Kang H, K JU, Chang H, Kim S, Jung W. The mRNA and miRNA transcriptomic landscape of Panax ginseng under the high ambient temperature. BMC Systems Biology. 2018 Mar 19.
  • Kim I, Choi S, Kim S, BRCA-Pathway: a structural integration and visualization system of TCGA breast cancer data on KEGG pathways. BMC Bioinformatics. 2018 Feb 19.
Conference proceedings
  • Ahn H, Jung I, Chae H, Kang D, Jung W, Kim S. HTRgene: Integrating Multiple Heterogeneous Time-series Data to Investigate Cold and Heat Stress Response Signaling Genes in Arabidopsis. The 2018 International Conference on Bioinformatics and Biomedicine (BIBM). 2018 Dec 4. [Invited to BMC Bioinformatics]
  • Rhee S, Seo S, Kim S. Hybrid Approach of Relation Network and Localized Graph Convolutional Filtering for Breast Cancer Subtype Classification. The 27th International Joint Conference on Artificial Intelligence (IJCAI). 2018 Jul 18.
  • L'Yi S, Jung D, Oh M, Kim B, Freishtat RJ, Giri M, Hoffman E, Seo J. miRTarVis+: Web-based interactive visual analytics tool for microRNA target predictions. Methods. 2017 Jul 15.
  • Ahn H, Jung I, Shin SJ, Park J, Rhee S, Kim JK, Jung W, Kwon HB, Kim S. Transcriptional Network Analysis Reveals Drought Resistance Mechanisms of AP2/ERF Transgenic Rice. Frontiers in Plant Science. 2017 Jun 15.
  • Lee S, Park Y, Kim S. MIDAS: Mining differentially activated subpaths of KEGG pathways from multi-class RNA-seq data. Methods. 2017 Jun 1.
  • Oh M, Rhee S, Moon JH, Chae H, Lee S, Kang J, Kim S, Literature-based condition-specific miRNA-mRNA target prediction. PLoS ONE. 2017 Mar 31.
  • Rhee S, Lim S, Kim S, Iterative segmented least square method for functional microRNA-mRNA module discovery in breast cancer. International Journal of Data Mining and Bioinformatics. 2017 Jan. [Link]
  • 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.
  • 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.
  • Shin SJ, Ahn H, Jung I, Rhee S, Kim S, Kwon HB, Novel drought-responsive regulatory coding and non-coding transcripts from Oryza Sativa L. Genes & Genomics. 2016 Jun 9.
  • Chae H, Lee S, Nephew KP, Kim S, Subtype-specific CpG island shore methylation and mutation patterns in 30 breast cancer cell lines. BMC Systems Biology, 2016 Dec 23.
  • Jung I, Ahn H, Shin SJ, Kim J, Kwon HB, Jung W, Kim S. Clustering and evolutionary analysis of small RNAs identify regulatory siRNA clusters induced under drought stress in rice. BMC Systems Biology, 2016 Dec 23.
  • 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.
  • Park Y, Lim S, Nam J, Kim S. Measuring intratumor heterogeneity by network entropy using RNA-seq data, Scientific Reports, 2016 Nov 24.
  • Hur B, Lim S, Chae H, Seo S, Lee S, Kang J, Kim S. CLIP-GENE: a web service of the condition specific context-laid integrative analysis for gene prioritization in mouse TF knockout experiments. Biology Direct, 2016 Nov 1.
  • Lim S, Park Y, Hur B, Kim M, Han W, Kim S. Protein interaction network (PIN)-based breast cancer subsystem identification and activation measurement for prognostic modeling. Methods. 2016 Nov 1.
  • Park J, Hur B, Rhee S, Lim S, Kim M, Kim K, Han W, Kim S. Information theoretic sub-network mining characterizes breast cancer subtypes in terms of cancer core mechanisms. Journal of Bioinformatics and Computational Biology. 2016 Oct 7.
  • Lee CJ, Ahn H, Lee SB, Shin J, Park WY, Kim JI, Lee J, Ryu H, Kim S, 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. BMC Medical Genomics. 2016 Aug 12.
  • Chae H, Lee S, Seo S, Jung D, Chang H, Nephew KP, Kim S. BioVLAB-mCpG-SNP-EXPRESS: A system for multi-level and multi-perspective analysis and exploration of DNA methylation, sequence variation (SNPs), and gene expression from multi-omics data. Methods. 2016 Jul 28.
  • Jeong HM, Lee S, Chae H, Kim R, Kwon MJ, Oh E, Choi YL, Kim S, Shin YK. Efficiency of methylated DNA immunoprecipitation bisulphite sequencing for whole-genome DNA methylation analysis. Epigenomics. 2016 Jun 8.
  • Jang Y, Yu N, Seo J, Kim S, Lee S, MONGKIE: an integrated tool for network analysis and visualization for multi-omics data. Biology Direct. 2016 Mar 18.
  • Jo K, Jung IU, Moon JH, Kim S, Influence maximization in time bounded network identifies transcription factors regulating perturbed pathways. Bioinformatics. 2016 Jun 15.
  • Kim M, Hur B, Kim S. RDDpred: a condition-specific RNA-editing prediction model from RNA-seq data. BMC Genomics. 2016 Jan 11.
  • Hur B, Chae HJ, Kim S. Combined analysis of gene regulatory network and SNP information enhances identification of potential gene markers in mouse knockout studies with small number of samples. BMC Medical Genomics. 2015 8(Suppl 2): S10.
  • Sandhan T, Yoo YJ, Choi JY, Kim S., Graph Pyramid Approach for Protein Classification. BMC Medical Genomics. 2015 8(Suppl 2):S12.
  • Kim Y, Kang YS, Lee NY, Kim KY, Hwang YJ, Kim HW, Rhyu IJ, Her S, Jung MK, Kim S, Lee CJ, Ko S, Kowall NW, Lee SB, Lee J, Ryu H, Uvrag targeting by Mir125a and Mir351 modulates autophagy associated with Ewsr1 deficiency., Autophagy, 2015 May 5
  • Yerrapragada S, Shukla A, Hallsworth-Pepin K, Choi K, Wollam A, Clifton S, Qin X, Muzny D, Raghuraman S, Ashki H, Uzman A, Highlander SK, Fryszczyn BG, Fox GE, Tirumalai MR, Liu Y, Kim S, Kehoe DM, Weinstock GM., Extreme Sensory Complexity Encoded in the 10-Megabase Draft Genome Sequence of the Chromatically Acclimating Cyanobacterium Tolypothrix sp. PCC 7601.Genome Announc. 2015 May 7;3(3)
  • Rhee S, Chae H, Kim S. PlantMirnaT: miRNA and mRNA integrated analysis fully utilizing characteristics of plant sequencing data. Methods. 2015 Jul 15;83:80-7.
  • Chae H, Rhee SM, Nephew KP, Kim S. BioVLAB-MMIA-NGS: MicroRNA-mRNA integrated analysis using high throughput sequencing data. Bioinformatics, 2014.
  • An JH, Kim KS, Chae HJ, Kim S, DegPack: A web package using a non-parametric and information theoretic algorithm to identify differentially expressed genes in multiclass RNA-seq samples, Methods, 2014.
  • 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.
  • Jung IU, Park JC, Kim S. piClust: A density based piRNA clustering algorithm. Computational Biology and Chemistry. 50. 60-67. 2014 Jan 23. doi: 10.1016/j.compbiolchem.2014.01.008.
  • Kim KY, Hwang YJ, Jung MK, Choe J, Kim Y, Kim S, Lee CJ, Ahn H, Lee J, Kowall NW, Kim YK, Kim JI, Lee SB, Ryu H. A multifunctional protein EWS regulates the expression of Drosha and microRNAs. Cell Death Differ. 2013 Nov 1. doi: 10.1038/cdd.2013.144.
  • Rhee J, Kim K, Chae H, Evans J, Yan P, Zhang B, Gray J, Spellman P, Huang T, Nephew K and Kim S. Integrated Analysis of Genome-wide DNA Methylation and Gene Expression Profiles in Molecular Subtypes of Breast Cancer, Nucleic Acids Res. 2013 July 2;41(18):8464-8474.doi: 10.1093/nar/gkt643
  • Rhee SM, Park JW, and Kim S. Computational regulatory network construction from microRNA and transcription factor perspectives. ACM SIG Bio Record, Volume 3, Issue 3, May 2013 ISSN 2159-1210. [Link]
  • Lee KY and Kim S, Designing Discriminative Spatial Filter Vectors in Motor Imagery Brain–Computer Interface, International Journal of Imaging Systems and Technology, Vol. 23, No. 2, 2013, 147–151.
  • Chae HJ, Park, JW, Lee SW, Nephew KP, Kim S. Comparative Analysis Using K-mer and K-flank Patterns Provides Evidence for CpG Island Sequence Evolution in Mammalian Genomes, Nucleic Acids Res. 2013 May 1;41(9):4783-91.
  • An JH, Kim KS, Rhee SM, Chae HJ, Nephew KP, Kim S. Genome-wide analysis and modeling of DNA methylation susceptibility in 30 breast cancer cell lines by using CpG flanking sequences. Journal of Bioinformatics and Computational Biology. 2013 Jun;11(3):1341003. doi: 10.1142/S0219720013410035.
  • Chae H, Jung I, Lee H, Marru S, Lee SW and Kim S. Bio and Health informatics meets Cloud : BioVLab as an example. Health Information Science and Systems 2013, 1:6
  • Nam S, Long X, Kwon C, Kim S, Nephew KP. An integrative analysis of cellular contexts, miRNAs and mRNAs reveals network clusters associated with antiestrogen-resistant breast cancer cells. BMC Genomics. 2012 Dec 27;13:732.
  • Rao X, Evans J, Chae H, Pilrose J, Kim S, Yan P, Huang RL, Lai HC, Lin H, Liu Y, Miller D, Rhee JK, Huang YW, Gu F, Gray JW, Huang TM, Nephew KP. CpG island shore methylation regulates caveolin-1 expression in breast cancer. Oncogene, 2012 Nov 5. doi: 10.1038/onc.2012.474.
  • Lee H, Yang Y, Chae H, Nam S, Choi D, Tangchaisin P, Herath C, Marru S, Nephew K, Kim S. BioVLAB-MMIA: A Cloud Environment for microRNA andmRNA Integrated Analysis (MMIA) on Amazon EC2, IEEE Transactions on NanoBioscience, Volume 11, Issue 3, Sept. 2012 ISSN 1536-1241. doi:10.1109/TNB.2012.2212030
  • Pejaver VR, An J, Rhee SM, Bhan A, Choi JH, Liu B, Lee H, Brown PJ, Kysela D, Brun YV, Kim S. GeneclusterViz: a tool for conserved gene cluster visualization, exploration and analysis, Bioinformatics, 2012, 28(11), 1527-1529.
  • Gupta R, Kim S, Taylor MW. Suppression of ribosomal protein synthesis and protein translation factors by Peg-interferon alpha/ribavirin in HCV patients blood mononuclear cells (PBMC), Journal of Translational Medicince, 2012 10:54.
  • Yang Y, Nephew NP, Kim S. A Novel K-mer Mixture Logistic Regression for Methylation Susceptibility Modeling of CpG Dinucleotides in Human Gene Promoters, BMC Bioinformatics, 2012, 13(suppl 3) S15.
  • Hollenhorst PC, Ferris MW, Hull MA, Chae H, Kim S, Graves BJ. Oncogenic ETS proteins mimic activated RAS/MAPK signaling in prostate cells. Genes Dev. 2011 Oct 15;25(20):2147-57.
  • Choi KM and Kim S. Sequence-Based Enzyme Catalytic Domain Prediction Using Clustering and Aggregated Mutual Information Content. Journal of Bioinformatics and Computational Biology. Vol. 9, No. 5 (2011) 1–15 (IEEE HISB extended version)
  • Pejaver V and Kim S. Gene Cluster Profile Vectors: a method to infer functionally related gene sets by grouping proximity-based gene clusters. BMC Genomics 2011, 12(Suppl 2):S2 (27 July 2011
  • Choi K, Kim S. Building Interacting Partner Predictors Using Co-varying Residue Pairs Between Histidine Kinase and Response Regulator Pairs of 48 Bacterial Two-Component Systems, Proteins, 2011 Apr;79(4):1118-31
  • Lu YK, Marden J, Han M, Swingley WD, Mastrian SD, Chowdhury SR, Hao J, Helmy T, Kim S, Kurdoglu AA, Matthies HJ, Rollo D, Stothard P, Blankenship RE, Bauer CE, Touchman JW. Metabolic flexibility revealed in the genome of the cyst-forming alpha-1 proteobacterium Rhodospirillum centenum. BMC Genomics. 2010 May 25;11:325.
  • Kim S. Data mining for the study of disease genes and proteins, Artif Intell Med. (editorial) 2010 Jul;49(3):133-4.
  • Choi JH, Li Y, Guo J, Kramer R, Rauch T, Macmil S, Wiley G, Bennett L, Schnabel J, Taylor K, Kim S, Dong X, Sreekumar A, Pfeifer G, Roe B, Caldwell C, Bhalla H, Shi H. Genome-wide DNA methylation maps in follicular lymphoma cells determined by methylation-enriched bisulfite sequencing, PLoS ONE, 2010 Sep 29;5(9)
  • Rho M, Schaack S, Gao X, Kim S, Lynch M, Tang H. LTR retroelements in the genome of Daphnia pulex, BMC Genomics, 2010 Jul 9;11:425.
  • Yang Y, Gibert D., Kim S. Confidence Score for Genome Annotation: A Genome Comparison Approach Bioinformatics, 26:22-29, 2010
  • Li M, Balch C, Montgomery JS, Jeong MK, Chung JH, Yan P, Huang T H-M, Kim S, Nephew KP. Integrated Analysis of DNA Methylation and Gene Expression Reveals Specific Signaling Pathways Associated with Platinum Resistance in Ovarian Cancer BMC Medical Genomics, 2009, 2:34
  • Rho M, Zhou M, Gao X, Kim S, Tang H, Lynch M. Independent Mammalian Genome Contractions Following the KT Boundary. Genome Biology and Evolution 2009:2
  • Nam S, Li M, Choi K, Balch C, Kim S, Nephew KP. MicroRNA and mRNA integrated analysis (MMIA): a web tool for examining biological functions of microRNA expression. Nucleic Acids Res. 2009 May 6.
  • Xin F, Li M, Balch C, Thomson M, Fan M, Liu Y, Hammond SM, Kim S, Nephew KP. Computational Analysis of MicroRNA Profiles and Their Target Genes Suggests Significant Involvement in Breast Cancer Antiestrogen Resistance. Bioinformatics. 2009 Feb 15;25(4):430-4.
  • Hu M, Choi K, Su W, Kim S, Yang J. A Gene Pattern Mining Algorithm Using Mutable Sets for Prokaryotes. BMC Bioinformatics, 2008, 9:124
  • Choi JH, Kim S, Tang H, Andrews J, Gilbert DG, Colbourne JK. A machine-learning approach to combined evidence validation of genome assemblies. Bioinformatics. 2008 Mar 15;24(6):744-50.
  • Choi K, Kim S. ComPath: comparative enzyme analysis and annotation in pathway/subsystem contexts. BMC Bioinformatics. 2008 Mar 6;9:145.
  • Li M, Paik HI, Balch C, Kim Y, Li L, Huang TH, Nephew KP, Kim S. Enriched transcription factor binding sites in hypermethylated gene promoters in drug resistant cancer cells. Bioinformatics. 2008 Aug 15;24(16):1745-8.
  • Kim S, Wang Z, Dalkilic M. iGibbs: improving Gibbs motif sampler for proteins by sequence clustering and iterative pattern sampling. Proteins. 2007 Feb 15;66(3):671-81.
  • Rho M, Choi JH, Kim S, Lynch M, Tang H. De novo identification of LTR retrotransposons in eukaryotic genomes. BMC Genomics. 2007 Apr 3;8:90.
  • Bae SH, Tang H, Wu J, Xie J, Kim S. dPattern: transcription factor binding site (TFBS) discovery in human genome using a discriminative pattern analysis. Bioinformatics. 2007 Oct 1;23(19):2619-21.
  • Hemmerich C, Kim S. A Study of Residue Correlation within Protein Sequences and Its Application to Sequence Classification. EURASIP J Bioinform Syst Biol. 2007:87356.
  • Tsukahara T, Kim S, Taylor MW. REFINEMENT: a search framework for the identification of interferon-responsive elements in DNA sequences--a case study with ISRE and GAS. Comput Biol Chem. 2006 Apr;30(2):134-47.
  • Wei SH, Balch C, Paik HH, Kim YS, Baldwin RL, Liyanarachchi S, Li L,Wang Z. Wan JC, Davuluri RV, Karlan BY, Gifford G, Brown R, Kim S, Huang TH, Nephew KP. Prognostic DNA methylation biomarkers in ovarian cancer. Clin Cancer Res. 2006 May 1;12(9):2788-94.
  • Li L, Cheng AS, Jin VX, Paik HH, Fan M, Li X, Zhang W, Robarge J, Balch C, Davuluri RV, Kim S, Huang TH, Nephew KP. A mixture model-based discriminate analysis for identifying ordered transcription factor binding site pairs in gene promoters directly regulated by estrogen receptor-alpha. Bioinformatics. 2006 Sep 15;22(18):2210-6.
  • Song B, Choi JH, Chen G, Szymanski J, Zhang GQ, Tung AK, Kang J, Kim S, Yang J. ARCS: an aggregated related column scoring scheme for aligned sequences. Bioinformatics. 2006 Oct 1;22(19):2326-32.
  • Kim S, Choi JH, Saple A, Yang J. A hybrid gene team model and its application to genome analysis. J Bioinform Comput Biol. 2006 Apr;4(2):171-96.
  • Kim S, Lee J. BAG: a graph theoretic sequence clustering algorithm. Int J Data Min Bioinform. 2006;1(2):178-200.
  • Lee D, Choi JH, Dalkilic MM, Kim S. COMPAM :visualization of combining pairwise alignments for multiple genomes. Bioinformatics. 2006 Jan 15;22(2):242-4.
  • Nobuta K, Ashfield T, Kim S, Innes RW. Diversification of non-TIR class NB-LRR genes in relation to whole-genome duplication events in Arabidopsis. Mol Plant Microbe Interact. 2005 Feb;18(2):103-9.
  • Choi K, Ma Y, Choi JH, Kim S. PLATCOM: a Platform for Computational Comparative Genomics. Bioinformatics. 2005 May 15;21(10):2514-6.
  • Balch C, Montgomery JS, Paik HI, Kim S, Kim S, Huang TH, Nephew KP. New anti-cancer strategies: epigenetic therapies and biomarkers. Front Biosci. 2005 May 1;10:1897-931. Review.
  • Choi JH, Cho HG, Kim S. GAME: a simple and efficient whole genome alignment method using maximal exact match filtering. Comput Biol Chem. 2005 Jun;29(3):244-53.
  • Wood DW. ... Kim S. ... Nester EW. The Genome of Agrobacterium tumefaciens C58: Insights into the evolution and biology of a natural genetic engineer,'' Science, ISSN 0036-8075, Dec 14 2001: 2317-2323
  • Kim S. A New String Matching Algorithm Using Partitioning and Hashing Efficiently. The ACM Journal of Experimental Algorithmics, Vol 4, 1999
  • Kim S. and Segre AM. AMASS: A Structured Pattern Matching Approach to Shotgun Sequence Assembly. JournalofComputationalBiology, ISSN 1066-5277, Vol 6 (2), Mary Ann Liebert Press 1999, pp. 163-186.
  • Kang D, Ahn H, Lee S, Lee CJ, Hur J, Jung W, Kim S. Identifying stress-related genes and predicting stress types in Arabidopsis using logical correlation layer and CMCL loss through time-series data. The 2018 International Conference on Bioinformatics and Biomedicine (BIBM). 2018 Dec 4. [Invited to BMC Genomics]
  • Ahn H, Chae H, Kim S, Integration of heterogeneous time series gene expression data by clustering on time dimension, 2017 IEEE International Conference on Big Data and Smart Computing (BigComp 2017)
  • Lee S, Moon JH, Park Y, Kim S, Flow maximization analysis of cell cycle pathway activation status in breast cancer subtypes, 2017 IEEE International Conference on Big Data and Smart Computing (BigComp 2017)
  • Rhee S, Lim S, Kim S, Iterative segmented least square method for functional microRNA-mRNA module discovery in breast cancer. 2016 IEEE International Conference On Bioinformatics and Biomedicine (BIBM 2016), Shenzhen, China
  • Lee CJ, Ahn H, Lee SB, Shin JY, Park WY, Kim JI, Lee JH, Ryu H, Kim S. Integrated analysis of omics data using microRNA-target mRNA network and PPI network reveals regulation of Gnai1 function in the spinal cord of EWS KO mice. The 5th Translational Bioinformatics Conference (TBC 2015), Tokyo, Japan.
  • Kim HJ, Moon JH, Shin JS, Kim BG, Kim JS, Min BH, Jo K, Kang SJ, Byun N, Phuong T, Kim JM, Kim S, Park CG. A new bioinformatics analysis can reveal intestinal infection as a cause of graft rejection in islet xenotransplantation in non-human primate. Presented at the Annual Meeting, American Association of Immunologist, May 2015, New Orleans, LA
  • 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
  • Hur B, Chae H and Kim S, Combined analysis of gene regulatory network and SNP information enhances identification of potential gene markers in mouse knockout studies with small number of samples. The 8th International Conference on Systems Biology and the 4th Translational Bioinformatics Conference (ISB/TBC 2014), Qingdao, October 2014
  • An JH, Kim KS and Kim S. An algorithm for identifying differentially expressed genes in multiclass RNA-seq samples. International Conference on Big Data and Smart Computing (BIGCOMP), Bangkok, January 2014.
  • Jung IU, Park JC and Kim S. piClust: A density based piRNA clustering algorithm. Asia Pacific Bioinformatics Conference (APBC) 2014. Accepted in October 2013.
  • Yoo YJ, Sandhan T, Choi J, and Kim S. Towards Simultaneous Clustering and Motif-Modeling for a Large Number of Protein Families. IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM) Workshop on Biomolecular Network Analysis (IWBNA), Shanghai, December 2013
  • Lee KY, Kim S. Discriminative spatial pattern vectors selection for motor imagery classification. Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (SMC) 2012: 981-984
  • Marru S, Chae H, Tangchaisin P, Kim S, Pierce M, Nephew K. Transitioning BioVLab cloud workbench to a science gateway. Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery. No. 40. 2011.
  • Lee HR, Yang Y, Chae HJ, Nam SY, Choi DH, Tangchaisin P, Herath C, Marru S, Nephew K, and Kim S. BioVLAB-MMIA: A Reconfigurable Cloud Computing Environment for microRNA and mRNA Integrated Analysis. IEEE International Conference on Bioinformatics and Biomedicine (IEEE BIBM 2011).
  • Choi KM and Kim S. Sequence-Based Enzyme Catalytic Domain Prediction Using Clustering and Aggregated Mutual Information Content. IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology (HISB), 2011
  • Pejaver V and Kim S. Gene Cluster Profile Vectors: A Novel Method to Infer Functional Coupling Using Both Gene Proximity and Co-occurrence Profiles. Proc IEEE International Conference on Bioinformatics and Biomedicine (BIBM) 2010, pp 29-34, Hong Kong, December 2010.
  • Chae H, Ashki H, Chio KM, Kim S. EGGSlicer: Predicting biologically meaningful gene sets from gene clusters using gene ontology information, Proc. ACM Conference on Bioinformatics and Computational Biology, 2010
  • Yang Y, Kim S. Issues in Comparing Gene Function Annotation in Text, ACM SIGDOC Conference, pp 227-232, 2009
  • Kim S, Li M, Paik H, Nephew K, Shi H, Kramer R, Xu D, Huang TH. Predicting DNA methylation susceptibility using CpG flanking sequences. Pac Symp Biocomput. 2008:315-26.
  • Yang Y, Choi JY, Choi K, Gannon D, Pierce P, and Kim S. BioVLAB-Microarray: Microarray Data Analysis in Virtual Environment. Proc IEEE E-science, December 2008
  • Choi JY, Yang Y, Kim S, and Gannon D. VLAB-Proteins: a Collaborative Virtul Lab for Protein Sequence Anlaysis. Proc IEEE Workshop on High-Throughput Data Analysis for Proteomics and Genomics, pp 183-190, November 2-5, 2007, San Jose, CA
  • Choi K, Yang Y, and Kim S. CLASSEQ: Classification of Multiple Sequences via Comparative Analysis of Multiple Genomes. Proc International Workshop on Machine Learning in Biomedicine and Bioinformatics (MLBB) with The Sixth International Conference on Machine Learning and Applications (ICMLA), pp 554-559, December 13-15, 2007
  • Patwardhan R, Tang H, Kim S, and Dalkilic M. An approximate de Bruijn graph approach to multiple local alignment and motif discovery in protein sequences. Lecture Note in Bioinformatics 4316, Springer 2007
  • Bhan A, Maryada BK, Choi K, and Brun Y, Kim S. EGGS: Extraction of Gene clusters by iteratively using Genome context based Sequence matching techniques. Proc IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp 23-28 November 2-5, 2007, San Jose, CA
  • Sheth H, Kim S. Motif Discovery for Proteins By Subsequence Clustering The 5th ACM SIGKDD Workshop on Data Mining in Bioinformatics August 2005
  • Kim S. A System Design Paradigm to Deliver a Genome Comparison System on the Web. Microsoft E-science Workshop, October 2005.
  • Choi KM, Choi JH, Saple A, Wang Z, Lee J, Kim S. PLATCOM: Current Status and Plan for the Next Stages. DILS, LNCS 3615, 300-304, 2005
  • Kim S, Choi JH, Yang J. Gene teams with relaxed proximity constraint. Proc IEEE Comput Syst Bioinform (CSB) Conf. 2005:44-55.
  • Choi JH, Choi KM, Cho HG, Kim, S. Multiple Genome Alignment by Clustering Pairwise Matches,'' Jens Lagergren (Ed.): Comparative Genomics, RECOMB 2004 International Workshop. Lecture Notes in Computer Science 3388, ISSN 0302-9743, Springer 2005
  • Wang Z, Dalkilic M, and Kim S. Guiding Motif Discovery by Iterative Pattern Refinement. ACM SAC Bioinformatics Track 2004, March 14-17, Nicosia, Cyprus, 2004.
  • Gunduz I, Zhao S, Dalkilic M and Kim S. Motif Discovery from A Large Number of Sequences: A Case Study with Disease Resistance Genes in Arabidopsis thaliana. The 2003 International Conference on Mathematics and Engineering Techniques in Medicine and Biological Sciences (METMBS'03) June 23-26, 2003, Las Vegas, Nevada, USA.
  • Liao L. Kim S. and Tomb JF. Genome Comparisons Based on Profiles of Metabolic Pathways. Proc . of Sixth International Conference on Knowledge-Based Intelligent Information & Engineering Systems (KES 2002) September 2002 Crema, Italy
  • Kim S. Liao L. and Tomb JF. A Probabilistic Approach to Sequence Assembly Validation. ACM SIGKDD Workshop on Data Mining in Bioinformatics (BioKDD2001), 2001, pp 38-43
  • Kim S. and Kim YG. A Fast Multiple String-Pattern Matching Algorithm. Proc. of 17th AoM/IAoM Conference on Computer Science, August 1999,
  • Kim S. and Zhang H. ModGen: Theorem Proving by Model Generation. Proceedings of National Conferenceon Artificial Intelligence(AAAI), 1994, Seattle, WA. MIT Press, pp. 162-167.
  • Eom JH. Kim S. Kim WK. and Lee CS. C-INFO: C Program Information Management System. IFAC/IFIPWorkshopontheExperiencewiththeManagementofSoftwareProjects, 1989.
  • Kim S. and Moon SC. Nonredundant Allocation of Files in Distributed Systems. Proceedings of the IEEE Region10 Conference, 1987. ISSN 1078-0432, 2006 12: 2788-2794.
  • 안용주, 김선. 딥러닝 기반의 DNA 서열 자기참조 모델링을 이용한 전사인자-DNA 결합 친화도 예측, 한국정보과학회 2017 한국소프트웨어종합학술대회 논문집, Vol.2017, pp.939-941.
  • 손승현, 안홍렬, 김선. 딥러닝을 통한 유전자 온톨로지 거리의 추론, 한국정보과학회 2017 한국소프트웨어종합학술대회 논문집, Vol.2017, pp.994-956.
  • 임애란, 강혜진, 김선. 히스톤 변이 마크를 이용한 인핸서 영역 분류 순환 신경 망 모델, 2017년 한국컴퓨터종합학술대회 논문집, Vol.2017, pp.966-968.
  • 김인영, 최새미, 김선, 관계형 데이터베이스 모델링과 REST API 기반 사용자 친화적 생물학적 데이터 추출 시스템, 한국정보과학회 2016년 동계학술발표회 논문집, Vol.2016, No.12, pp. 1195-1197
  • 강혜진, 정인욱, 정우석, 김선. Spherical vector clustering 기법과 Support Vector Machine을 이용한 한발관련 표현형이 다른 벼의 복수 시계열 Next Generation Sequencing 테이터의 분석, 한국정보과학회 2015년 동계학술발표회 논문집, Vol.2015, pp.651-653.
  • 강동원, 안홍렬, 정우석, 김선. 이질적 시계열 유전자 발현 데이터의 통합 분석 문제의 정의 및 애기장대에서의 저온 스트레스 반응 유전자 검출 알고리즘 개발, 한국정보과학회 2015년 동계학술발표회 논문집, Vol.2015, No.12, pp.648-650.
  • 조겨리, 김선. 네트워크를 이용한 시계열 유전체 분석 기법의 연구 동향, 정보과학회지, Vol.32, No. 10, 2014년 10월, pp.22-27.
  • 서석준, 오민식, 정인욱, 채희준, 김선. BioVLAB-클라우드 기반의 생물정보학 분석 시스템, 정보과학회지, Vol.31, No.3, 2013년 3월, pp.108-114.
  • Lee CJ, Evans J, Kim KS, Chae HJ, and Kim S. Determining the Effect of DNA Methylation on Gene Expression in Cancer Cells. Gene Function Analysis, Methods in Molecular Biology, vol. 1101, Michael F. Ochs edited, Springer, 2013.
  • Pejaver VR, Lee HW, and Kim S. Gene cluster prediction and its application to genome annotation. In Omics approaches for protein function prediction, Kihara D edited. Springer 2010. ISBN 978-94-007-0881-5
  • Chio JH, Kim S, Tang H, and Pop M. Computational Approaches for Genome Assembly Validation. Biological Data Mining, Chen and Lonardi edited, Chapman and Hall/CRC Press, 2009
  • Choi JH, Kim S, Tang S, and Pop M. Computational Approaches for Genome Assembly Validation. Biological Data Mining, Jake Y. Chen and Stefano Lonardi, ed. Chapman and Hall/CRC Press, 2009
  • Choi K, Yang Y, Kim S. CGAS: a comparative genome annotation system. Methods Mol Biol. 2007;395:133-46.
  • Kim S, Tang H, Mardis ER. Advances in Genome Sequencing Technology and Algorithms. Artech House, 2007
  • Kim S. Graph Theoretic Sequence Clustering Algorithms and Their Applications to Genome Comparison. Chapter 4 in Computational Biology and Genome Informatics edited by Jason T. L. Wang, Cathy H. Wu, and Paul Wang, World Scientific, 2003