Yu Li (李煜)

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	总计	2019 年至今
引用	2982	2932
h 指数	30	29
i10 指数	51	51

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Xin GaoProfessor, Computer Sciences; Director, Computational Bioscience Research Center在 kaust.edu.sa 的电子邮件经过验证
Ramzan UmarovPostdoctoral researcher, RIKEN在 riken.jp 的电子邮件经过验证
Sheng WangZelixir Biotech在 zelixir.com 的电子邮件经过验证
Yixuan WangPh.D. Candidate in CSE, Chinese University of Hong Kong在 cse.cuhk.edu.hk 的电子邮件经过验证
Lizhong Ding (丁立中)Inception Institute of Artificial Intelligence (IIAI), Abu Dhabi, UAE在 inceptioniai.org 的电子邮件经过验证
Le SongBiomap, Mohamed bin Zayed University of Artificial Intelligence在 biomap.com 的电子邮件经过验证
Irwin KingThe Chinese University of Hong Kong在 cse.cuhk.edu.hk 的电子邮件经过验证
Licheng ZongPh.D. Candidate@CUHK, Visiting@EMBL-EBI & University of Cambridge在 ebi.ac.uk 的电子邮件经过验证
hiroyuki kuwaharaResearch Scientist at KAUST在 kaust.edu.sa 的电子邮件经过验证
Liang HongPhD at The Chinese University of Hong Kong在 link.cuhk.edu.hk 的电子邮件经过验证
Qingxiong TanComputer Science & Engineering, Chinese University of Hong Kong在 cuhk.edu.hk 的电子邮件经过验证
Jiayang ChenCUHK在 cuhk.edu.hk 的电子邮件经过验证
Mo LiKing Abdullah University of Science and Technology (KAUST)在 kaust.edu.sa 的电子邮件经过验证
wei chenProfessor of Systems Biology, Southern University of Science and Technology在 sustech.edu.cn 的电子邮件经过验证
Hanjun DaiGoogle DeepMind在 google.com 的电子邮件经过验证
Xinshi ChenGeorgia Institution of Technology在 bytedance.com 的电子邮件经过验证
Yuqi ChengPhD student @ College of Computing, Georgia Institute of Technology在 gatech.edu 的电子邮件经过验证
Ting-Fung ChanSchool of Life Sciences, The Chinese University of Hong Kong在 cuhk.edu.hk 的电子邮件经过验证
Siyuan ChenKING ABDULLAH UNIVERSITY/SCIENCE/TECHNOL在 kaust.edu.sa 的电子邮件经过验证
Xuhui HuangHirschfelder Chair in Theoretical Chemistry, University of Wisconsin-Madison (previously at HKUST)在 chem.wisc.edu 的电子邮件经过验证

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Yu Li (李煜)

Assistant Professor, Computer Science & Engineering, Chinese University of Hong Kong

在 cse.cuhk.edu.hk 的电子邮件经过验证 - 首页

Deep Learning Bioinformatics Healthcare Machine Learning


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Deep learning in bioinformatics: Introduction, application, and perspective in the big data era Y Li, C Huang, L Ding, Z Li, Y Pan, X Gao Methods 166, 4-21, 2019	390	2019
DEEPre: sequence-based enzyme EC number prediction by deep learning Y Li, S Wang, R Umarov, B Xie, M Fan, L Li, X Gao Bioinformatics 34 (5), 760-769, 2018	285	2018
Progressive-hint prompting improves reasoning in large language models C Zheng, Z Liu, E Xie, Z Li, Y Li arXiv preprint arXiv:2304.09797, 2023	120	2023
RNA secondary structure prediction by learning unrolled algorithms X Chen, Y Li, R Umarov, X Gao, L Song arXiv preprint arXiv:2002.05810, 2020	112	2020
mlDEEPre: multi-functional enzyme function prediction with hierarchical multi-label deep learning Z Zou, S Tian, X Gao, Y Li Frontiers in genetics 9, 714, 2019	110	2019
DeepSimulator: a deep simulator for Nanopore sequencing Y Li, R Han, C Bi, M Li, S Wang, X Gao Bioinformatics 34 (17), 2899-2908, 2018	110	2018
Promoter analysis and prediction in the human genome using sequence-based deep learning models R Umarov, H Kuwahara, Y Li, X Gao, V Solovyev Bioinformatics 35 (16), 2730-2737, 2019	103	2019
A self-adaptive deep learning algorithm for accelerating multi-component flash calculation T Zhang, Y Li, Y Li, S Sun, X Gao Computer Methods in Applied Mechanics and Engineering 369, 113207, 2020	98	2020
Modern deep learning in bioinformatics H Li, S Tian, Y Li, Q Fang, R Tan, Y Pan, C Huang, Y Xu, X Gao Journal of molecular cell biology 12 (11), 823-827, 2020	96	2020
A deep learning framework to predict binding preference of RNA constituents on protein surface JH Lam, Y Li, L Zhu, R Umarov, H Jiang, A Héliou, FK Sheong, T Liu, ... Nature communications 10 (1), 4941, 2019	96	2019
HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes Y Li, Z Xu, W Han, H Cao, R Umarov, A Yan, M Fan, H Chen, CM Duarte, ... Microbiome 9, 1-12, 2021	70	2021
H-NS uses an autoinhibitory conformational switch for environment-controlled gene silencing UF Shahul Hameed, C Liao, AK Radhakrishnan, F Huser, SS Aljedani, ... Nucleic acids research 47 (5), 2666-2680, 2019	64	2019
Interpretable RNA foundation model from unannotated data for highly accurate RNA structure and function predictions J Chen, Z Hu, S Sun, Q Tan, Y Wang, Q Yu, L Zong, L Hong, J Xiao, ... arXiv preprint arXiv:2204.00300, 2022	63	2022
Accelerating flash calculation through deep learning methods Y Li, T Zhang, S Sun, X Gao Journal of Computational Physics 394, 153-165, 2019	63	2019
Sequence2vec: a novel embedding approach for modeling transcription factor binding affinity landscape H Dai, R Umarov, H Kuwahara, Y Li, L Song, X Gao Bioinformatics 33 (22), 3575-3583, 2017	63	2017
Protein–RNA interaction prediction with deep learning: structure matters J Wei, S Chen, L Zong, X Gao, Y Li Briefings in bioinformatics 23 (1), bbab540, 2022	58	2022
DeepSimulator1. 5: a more powerful, quicker and lighter simulator for Nanopore sequencing Y Li, S Wang, C Bi, Z Qiu, M Li, X Gao Bioinformatics 36 (8), 2578-2580, 2020	57	2020
Learning to stop while learning to predict X Chen, H Dai, Y Li, X Gao, L Song International conference on machine learning, 1520-1530, 2020	55	2020
DeeReCT-PolyA: a robust and generic deep learning method for PAS identification Z Xia, Y Li, B Zhang, Z Li, Y Hu, W Chen, X Gao Bioinformatics 35 (14), 2371-2379, 2019	53	2019
On the decision boundary of deep neural networks Y Li, L Ding, X Gao arXiv preprint arXiv:1808.05385, 2018	52	2018

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