Seonwoo Min
机构: Applied Scientist, AWS Health AI
每年引用次数
引用次数
引用: 3,598
H-指数: 18
I10-指数 : 24
出版物: 28
Deep Recurrent Neural Network-Based Identification of Precursor microRNAs
Seunghyun Park , Sungroh Yoon , Hyun-Soo Choi , Seonwoo Min
neural information processing systems 30 2891 -2900
51
2017
Polyphonic Music Generation with Sequence Generative Adversarial Networks
Sungroh Yoon , Seonwoo Min , Uiwon Hwang , Sang-gil Lee
arXiv: Sound
9
2017
Neural Universal Discrete Denoiser
Byunghan Lee , Taesup Moon , Sungroh Yoon , Seonwoo Min
neural information processing systems 29 4772 -4780
10
2016
Recording of elapsed time and temporal information about biological events using Cas9.
Ji Hea Yu , Inkyung Jung , Hyongbum Henry Kim , Taeyoung Park
Cell 184 ( 4)
3
2021
Learned Embeddings from Deep Learning to Visualize and Predict Protein Sets
Burkhard Rost , Sungroh Yoon , Seonwoo Min , Kevin K. Yang
Current Protocols 1 ( 5)
41
2021
Protein transfer learning improves identification of heat shock protein families.
HyunGi Kim , Byunghan Lee , Sungroh Yoon , Seonwoo Min
PLOS ONE 16 ( 5)
2021
Learning-Based Instantaneous Drowsiness Detection Using Wired and Wireless Electroencephalography
Hyun-Soo Choi , Seonwoo Min , Siwon Kim , Ho Bae
IEEE Access 7 146390 -146402
2
2019
SpCas9 activity prediction by DeepSpCas9, a deep learning-based model with high generalization performance.
Hui Kwon Kim , Younggwang Kim , Sungtae Lee , Seonwoo Min
Science Advances 5 ( 11)
25
2019
Deep learning improves prediction of CRISPR–Cpf1 guide RNA activity
Hui Kwon Kim , Seonwoo Min , Myungjae Song , Soobin Jung
Nature Biotechnology 36 ( 3) 239 -241
109
2018
High-throughput analysis of the activities of xCas9, SpCas9-NG and SpCas9 at matched and mismatched target sequences in human cells.
Hui Kwon Kim , Sungtae Lee , Younggwang Kim , Jinman Park
Nature Biomedical Engineering 4 ( 1) 111 -124
27
2020
Predicting the efficiency of prime editing guide RNAs in human cells.
Hui Kwon Kim , Goosang Yu , Jinman Park , Seonwoo Min
Nature Biotechnology 39 ( 2) 198 -206
110
2021
Bag of Tricks for Electrocardiogram Classification With Deep Neural Networks
Seonwoo Min , Hyun-Soo Choi , Hyeongrok Han , Minji Seo
computing in cardiology conference 1 -4
2020
Prediction of the sequence-specific cleavage activity of Cas9 variants
Sungroh Yoon , Sung-Rae Cho , Hyongbum Henry Kim , Nahye Kim
Nature Biotechnology 38 ( 11) 1328 -1336
106
2020
Sequence-specific prediction of the efficiencies of adenine and cytosine base editors.
Myungjae Song , Hui Kwon Kim , Sungtae Lee , Younggwang Kim
Nature Biotechnology 38 ( 9) 1037 -1043
8
2020
Transformers meet Stochastic Block Models: Attention with Data-Adaptive Sparsity and Cost
Sungjun Cho , Seonwoo Min , Jinwoo Kim , Moontae Lee
Advances in Neural Information Processing Systems 35 24706 -24719
2022
Pure transformers are powerful graph learners
Jinwoo Kim , Dat Nguyen , Seonwoo Min , Sungjun Cho
Advances in Neural Information Processing Systems 35 14582 -14595
12
2022
Grounding visual representations with texts for domain generalization
Seonwoo Min , Nokyung Park , Siwon Kim , Seunghyun Park
Smpte Journal 37 -53
3
2022
Generation of a more efficient prime editor 2 by addition of the Rad51 DNA-binding domain
Myungjae Song , Jung Min Lim , Seonwoo Min , Jeong-Seok Oh
Nature communications 12 ( 1) 5617
25
2021
Improving generalization performance of electrocardiogram classification models
Hyeongrok Han , Seongjae Park , Seonwoo Min , Eunji Kim
Physiological Measurement 44 ( 5) 054003
2023
TargetNet: functional microRNA target prediction with deep neural networks
Seonwoo Min , Byunghan Lee , Sungroh Yoon
Bioinformatics 38 ( 3) 671 -677
5
2022