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2020 – today
- 2023
[j13]Jesse G. Meyer, Ryan J. Urbanowicz
, Patrick C. N. Martin, Karen O'Connor, Ruowang Li, Pei-Chen Peng, Tiffani J. Bright, Nicholas P. Tatonetti, Kyoung-Jae Won, Graciela Gonzalez-Hernandez, Jason H. Moore:
ChatGPT and large language models in academia: opportunities and challenges. BioData Min. 16(1) (2023)- 2022
- [j12]Kensuke Nakamura, Bong-Soo Sohn, Kyoung-Jae Won, Byung-Woo Hong:
Regularization in Network Optimization via Trimmed Stochastic Gradient Descent With Noisy Label. IEEE Access 10: 34706-34715 (2022) - [c5]Tomislav Dobricki, Xiahai Zhuang, Kyoung-Jae Won, Byung-Woo Hong:
Survey on unsupervised learning methods for optical flow estimation. ICTC 2022: 591-594 - 2021
- [j11]Guangzheng Weng, Junil Kim, Kyoung-Jae Won:
VeTra: a tool for trajectory inference based on RNA velocity. Bioinform. 37(20): 3509-3513 (2021) - 2020
- [c4]Shibiao Wan, Junil Kim, Yiping Fan, Kyoung-Jae Won:
Processing Millions of Single Cells by SHARP. BCB 2020: 62:1
2010 – 2019
- 2018
- [j10]David E. Condon, Phu V. Tran, Yu-Chin Lien, Jonathan Schug, Michael K. Georgieff, Rebecca A. Simmons, Kyoung-Jae Won:
Defiant: (DMRs: easy, fast, identification and ANnoTation) identifies differentially Methylated regions from iron-deficient rat hippocampus. BMC Bioinform. 19(1): 31:1-31:12 (2018) - 2015
- [j9]Nha Nguyen, An P. N. Vo, Inchan Choi, Kyoung-Jae Won:
A Stationary Wavelet Entropy-Based Clustering Approach Accurately Predicts Gene Expression. J. Comput. Biol. 22(3): 236-249 (2015) - 2014
- [j8]Nha Nguyen, An P. N. Vo, Kyoung-Jae Won:
A wavelet-based method to exploit epigenomic language in the regulatory region. Bioinform. 30(7): 908-914 (2014) - [j7]Nha Nguyen, An P. N. Vo, Kyoung-Jae Won:
A Wavelet Approach to Detect Enriched Regions and Explore Epigenomic Landscapes. J. Comput. Biol. 21(11): 846-854 (2014) - [c3]Nha Nguyen, Kyoung-Jae Won:
Gaussian derivative wavelets identify dynamic changes in histone modification. CIBCB 2014: 1-7 - 2013
- [j6]Kyoung-Jae Won, Craig Saunders, Adam Prügel-Bennett:
Evolving Fisher Kernels for Biological Sequence Classification. Evol. Comput. 21(1): 83-105 (2013)
2000 – 2009
- 2008
- [j5]Kyoung-Jae Won, Albin Sandelin, Troels Torben Marstrand, Anders Krogh:
Modeling promoter grammars with evolving hidden Markov models. Bioinform. 24(15): 1669-1675 (2008) - [j4]Kyoung-Jae Won, Iouri Chepelev, Bing Ren, Wei Wang:
Prediction of regulatory elements in mammalian genomes using chromatin signatures. BMC Bioinform. 9 (2008) - 2007
- [j3]Kyoung-Jae Won, Thomas Hamelryck, Adam Prügel-Bennett, Anders Krogh:
An evolutionary method for learning HMM structure: prediction of protein secondary structure. BMC Bioinform. 8 (2007) - 2006
- [j2]Kyoung-Jae Won, Adam Prügel-Bennett, Anders Krogh:
Evolving the structure of hidden Markov models. IEEE Trans. Evol. Comput. 10(1): 39-49 (2006) - 2005
- [c2]Kyoung-Jae Won, Thomas Hamelryck, Adam Prügel-Bennett, Anders Krogh:
Evolving hidden Markov models for protein secondary structure prediction. Congress on Evolutionary Computation 2005: 33-40 - 2004
- [j1]Kyoung-Jae Won, Adam Prügel-Bennett, Anders Krogh:
Training HMM structure with genetic algorithm for biological sequence analysis. Bioinform. 20(18): 3613-3619 (2004) - [c1]Kyoung-Jae Won, Adam Prügel-Bennett, Anders Krogh:
The Block Hidden Markov Model for Biological Sequence Analysis. KES 2004: 64-70
Coauthor Index
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