| Myeloid-derived suppressor cell subsets drive glioblastoma growth in a sex-specific manner D Bayik, Y Zhou, C Park, C Hong, D Vail, DJ Silver, A Lauko, G Roversi, ... Cancer discovery 10 (8), 1210-1225, 2020 | 157 | 2020 |
| Prediction of Alzheimer's disease based on deep neural network by integrating gene expression and DNA methylation dataset C Park, J Ha, S Park Expert Systems with Applications 140, 112873, 2020 | 117 | 2020 |
| Combinatorial feature embedding based on CNN and LSTM for biomedical named entity recognition M Cho, J Ha, C Park, S Park Journal of Biomedical Informatics, 103381, 2020 | 108 | 2020 |
| Novel deep learning model for more accurate prediction of drug-drug interaction effects G Lee, C Park, J Ahn BMC Bioinformatics 20 (Article number: 415), 2019 | 106 | 2019 |
| Integrative gene network construction to analyze cancer recurrence using semi-supervised learning C Park, J Ahn, H Kim, S Park PloS one 9 (1), e86309, 2014 | 73 | 2014 |
| Integrative gene network construction for predicting a set of complementary prostate cancer genes J Ahn, Y Yoon, C Park, E Shin, S Park Bioinformatics 27 (13), 1846-1853, 2011 | 47 | 2011 |
| IMIPMF: Inferring miRNA-disease interactions using probabilistic matrix factorization J Ha, C Park, C Park, S Park Journal of Biomedical Informatics 102, 2020 | 41 | 2020 |
| A crucial role of ROCK for alleviation of senescence-associated phenotype JT Park, HT Kang, CH Park, YS Lee, KA Cho, SC Park Experimental gerontology 106, 8-15, 2018 | 28 | 2018 |
| Improved prediction of miRNA-disease associations based on matrix completion with network regularization J Ha, C Park, C Park, S Park Cells 9 (4), 881, 2020 | 27 | 2020 |
| PMAMCA: prediction of microRNA-disease association utilizing a matrix completion approach J Ha, C Park, S Park BMC systems biology 13, 1-13, 2019 | 27 | 2019 |
| Disruption of nucleocytoplasmic trafficking as a cellular senescence driver JH Park, SJ Ryu, BJ Kim, HJ Cho, CH Park, HJC Choi, EJ Jang, EJ Yang, ... Experimental & Molecular Medicine 53 (6), 1092-1108, 2021 | 21 | 2021 |
| PISTON: Predicting drug indications and side effects using topic modeling and natural language processing G Jang, T Lee, S Hwang, C Park, J Ahn, S Seo, Y Hwang, Y Yoon Journal of Biomedical Informatics, 2018 | 19 | 2018 |
| MLMD: Metric learning for predicting MiRNA-disease associations J Ha, C Park IEEE Access 9, 78847-78858, 2021 | 17 | 2021 |
| Machine learning-based identification of genetic interactions from heterogeneous gene expression profiles C Park, JR Kim, J Kim, S Park PloS one 13 (7), e0201056, 2018 | 17 | 2018 |
| Systematic identification of differential gene network to elucidate Alzheimer's disease C Park, Y Yoon, M Oh, SJ Yu, J Ahn Expert Systems with Applications 85, 249-260, 2017 | 14 | 2017 |
| Radiomics Features of 18F-Fluorodeoxyglucose Positron-Emission Tomography as a Novel Prognostic Signature in Colorectal Cancer J Kang, JH Lee, HS Lee, ES Cho, EJ Park, SH Baik, KY Lee, C Park, ... Cancers 13 (3), 392, 2021 | 13 | 2021 |
| IMA: Identifying disease-related genes using MeSH terms and association rules J Kim, C Bang, H Hwang, D Kim, C Park, S Park Journal of biomedical informatics 76, 110-123, 2017 | 13 | 2017 |
| Myeloid-derived suppressor cell subsets drive glioblastoma growth in a sex-specific manner. Cancer Discov. 2020; 10: 1210–1225. doi: 10.1158/2159-8290 D Bayik, Y Zhou, C Park, C Hong, D Vail, DJ Silver, A Lauko, G Roversi, ... CD-19-1355.[Europe PMC free article][Abstract][CrossRef][Google Scholar], 0 | 13 | |
| Drug voyager: a computational platform for exploring unintended drug action M Oh, J Ahn, T Lee, G Jang, C Park, Y Yoon BMC bioinformatics 18, 1-13, 2017 | 12 | 2017 |
| Improved prediction of cancer outcome using graph-embedded generative adversarial networks C Park, I Oh, J Choi, S Ko, J Ahn IEEE Access 9, 20076-20088, 2021 | 9 | 2021 |
Sanghyun ParkProfessor of Computer Science, Yonsei UniversityVahvistettu sähköpostiosoite verkkotunnuksessa yonsei.ac.kr
