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Fu-Ying Dao

Showing results (1-10 of 31) with videos related to

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Imeta|June 13, 2024
DeepKla: An attention mechanism-based deep neural network for protein lysine lactylation site predictionHao Lv, Fu-Ying Dao, Hao Lin
Briefings in Bioinformatics|June 29, 2021
DeepIPs: comprehensive assessment and computational identification of phosphorylation sites of SARS-CoV-2 infection using a deep learning-based approachHao Lv, Fu-Ying Dao, Hasan Zulfiqar, et al.
Frontiers in Genetics|January 9, 2019
Recent Advances on the Machine Learning Methods in Identifying DNA Replication Origins in Eukaryotic GenomicsFu-Ying Dao, Hao Lv, Fang Wang, et al.
Research (Washington, D.C.)|November 21, 2022
Accurate Identification of DNA Replication Origin by Fusing Epigenomics and Chromatin Interaction InformationFu-Ying Dao, Hao Lv, Melissa J Fullwood, et al.
Biotechnology and Bioengineering|August 9, 2021
Advances in mapping the epigenetic modifications of 5-methylcytosine (5mC), N6-methyladenine (6mA), and N4-methylcytosine (4mC)Hao Lv, Fu-Ying Dao, Dan Zhang, et al.
Biotechnology and Bioengineering|February 2, 2022
Erratum for "Advances in mapping the epigenetic modifications of 5-methylcytosine (5mC), N6-methyladenine (6mA), and N4-methylcytosine (4mC)" (Vol. 118, Issue 11, pp. 4204-4216)Hao Lv, Fu-Ying Dao, Dan Zhang, et al.
Molecular Therapy. Nucleic Acids|January 11, 2021
A computational framework for identifying the transcription factors involved in enhancer-promoter loop formationLi Liu, Li-Rong Zhang, Fu-Ying Dao, et al.
Molecules (Basel, Switzerland)|August 15, 2018
Identifying Phage Virion Proteins by Using Two-Step Feature Selection MethodsJiu-Xin Tan, Fu-Ying Dao, Hao Lv, et al.
Computational and Structural Biotechnology Journal|May 22, 2020
Computational identification of N6-methyladenosine sites in multiple tissues of mammalsFu-Ying Dao, Hao Lv, Yu-He Yang, et al.
Briefings in Bioinformatics|December 6, 2020
DeepYY1: a deep learning approach to identify YY1-mediated chromatin loopsFu-Ying Dao, Hao Lv, Dan Zhang, et al.
Pageof 4

Showing results (1-10 of 31) with videos related to

Sort By:
Pageof 4
Imeta|June 13, 2024
DeepKla: An attention mechanism-based deep neural network for protein lysine lactylation site predictionHao Lv, Fu-Ying Dao, Hao Lin
Briefings in Bioinformatics|June 29, 2021
DeepIPs: comprehensive assessment and computational identification of phosphorylation sites of SARS-CoV-2 infection using a deep learning-based approachHao Lv, Fu-Ying Dao, Hasan Zulfiqar, et al.
Frontiers in Genetics|January 9, 2019
Recent Advances on the Machine Learning Methods in Identifying DNA Replication Origins in Eukaryotic GenomicsFu-Ying Dao, Hao Lv, Fang Wang, et al.
Research (Washington, D.C.)|November 21, 2022
Accurate Identification of DNA Replication Origin by Fusing Epigenomics and Chromatin Interaction InformationFu-Ying Dao, Hao Lv, Melissa J Fullwood, et al.
Biotechnology and Bioengineering|August 9, 2021
Advances in mapping the epigenetic modifications of 5-methylcytosine (5mC), N6-methyladenine (6mA), and N4-methylcytosine (4mC)Hao Lv, Fu-Ying Dao, Dan Zhang, et al.
Biotechnology and Bioengineering|February 2, 2022
Erratum for "Advances in mapping the epigenetic modifications of 5-methylcytosine (5mC), N6-methyladenine (6mA), and N4-methylcytosine (4mC)" (Vol. 118, Issue 11, pp. 4204-4216)Hao Lv, Fu-Ying Dao, Dan Zhang, et al.
Molecular Therapy. Nucleic Acids|January 11, 2021
A computational framework for identifying the transcription factors involved in enhancer-promoter loop formationLi Liu, Li-Rong Zhang, Fu-Ying Dao, et al.
Molecules (Basel, Switzerland)|August 15, 2018
Identifying Phage Virion Proteins by Using Two-Step Feature Selection MethodsJiu-Xin Tan, Fu-Ying Dao, Hao Lv, et al.
Computational and Structural Biotechnology Journal|May 22, 2020
Computational identification of N6-methyladenosine sites in multiple tissues of mammalsFu-Ying Dao, Hao Lv, Yu-He Yang, et al.
Briefings in Bioinformatics|December 6, 2020
DeepYY1: a deep learning approach to identify YY1-mediated chromatin loopsFu-Ying Dao, Hao Lv, Dan Zhang, et al.
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