Category / Seunghyun Park
hc-OTU: A Fast and Accurate Method for Clustering Operational Taxonomic Units based on Homopolymer Compaction
A genetic variant in SLC28A3, rs56350726, is associated with progression to castration-resistant prostate cancer in a Korean population with metastatic prostate cancer
Jung Ku Jo, Jong Jin Oh, Yong Tae Kim, Hong Sang Moon, Hong Yong Choi, Seunghyun Park, Jin-Nyoung Ho, Sungroh Yoon, Hae Young Park, and Seok-Soo Byun, Oncotarget, vol. 8, no. 57, pp. 96893-96902, November 2017.
Deep Recurrent Neural Network-Based Identification of Precursor microRNAs
Genetic risk score to predict biochemical recurrence after radical prostatectomy in prostate cancer: prospective cohort study
Jong Jin Oh, Seunghyun Park, Sang Eun Lee, Sung Kyu Hong, Sangchul Lee, Tae Jin Kim, In Jae Lee, Jin-Nyoung Ho, Sungroh Yoon, and Seok-Soo Byun, Oncotarget, vol. 8, no. 44, pp. 75979-75988, May 2017.
deepTarget: End-to-end Learning Framework for microRNA Target Prediction using Deep Recurrent Neural Networks
Byunghan Lee, Junghwan Baek, Seunghyun Park, and Sungroh Yoon, in Proceedings of the 7th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), pp. 434-442, Seattle, USA, October 2016.
Computational Prediction of Competitive Endogenous RNA
Genome-wide detection of allelic genetic variation to predict biochemical recurrence after radical prostatectomy among prostate cancer patients using an exome SNP chip
Jong Jin Oh, Seunghyun Park, Sang Eun Lee, Sung Kyu Hong, Sangchul Lee, Hak Min Lee, Jung Keun Lee, Jin-Nyoung Ho, Sungroh Yoon, and Seok-Soo Byun, Journal of Cancer Research and Clinical Oncology, vol. 141, no. 8, pp. 1493-1501, August 2015.