Hao Lin Hui Ding Research Scientist Students Postdoc Visiting Scholars Alumni Position

Fu-Ying Dao Ph.D.

Fu-Ying Dao is the postdoctoral fellow of School of Biological Sciences in Nanyang Technological University (adviser: Dr. Melissa Fullwood).

Google Scholar:  Fu-Ying Dao

E-mail: fuying.dao@ntu.edu.sg

ORCID: 0000-0001-5285-6044

Github: daofuying.github.io



2019-2023 Ph.D in Biomedical Engineering (adviser: Dr. Hao Lin), University of Electronic Science and Technology, Sichuan, China

2016-2019 M.S in Bioinformatics (adviser: Dr. Hao Lin), University of Electronic Science and Technology, Sichuan, China

2012-2016 B.S in Biotechnology (adviser: Dr. Hao Lin), University of Electronic Science and Technology, Sichuan, China

Academic Experience

2023-now Postdoctoral Scholar in Nanyang Technological University (adviser: Dr. Melissa Jane Fullwood)

2021-2022 Visiting Scholar in Nanyang Technological University and the Cancer Science Institute (adviser: Dr. Melissa Jane Fullwood)

Honours and Awards

The Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship, Nanyang Technologica University, 2023

Research interests

Her primary interests are in utilizing high-throughput sequencing data (eg. Hi-C and ChIA-PET) and deep learning algorithms to uncover epigenetic mechanisms associated with disease processes:

*Method development -- How to identify new biological insights from large amounts of available RNA-Seq data? -- Develop deep learning architecture to predict chromatin interactions of large cohorts of cell lines or clinical samples from RNA-Seq data

*The 3D structure of the genome -- Explore differences in the chromatin interactions of different samples to understand how chromatin interactions may be important for the identification of diagnostic and predictive biomarkers for epigenetically driven cancers

First-author Papers

11. Fu-Ying Dao, Meng-Lu Liu, Wei Su, Hao Lv, Zhao-Yue Zhang, Hao Lin*, Li Liu*. (2023) AcrPred: A hybrid optimization with enumerated machine learning algorithm to predict Anti-CRISPR proteins. International Journal of Biological Macromolecules, 228: 706-714. (2021 IF: 8.025) [Link]

10. Fu-Ying Dao, Hao Lv, Melissa J. Fullwood*, Hao Lin*. (2022) Accurate Identification of DNA Replication Origin by Fusing Epigenomics and Chromatin Interaction Information. Research, 2022: ID 9780293. (2021 IF: 11.036) [Link]

9. Fu-Ying Dao, Hao Lv, Zhao-Yue Zhang, Hao Lin*. (2021) BDselect: a package for k-mer selection based on binomial distribution. Current Bioinformatics, 17(3): 238-244(7). (2021 IF: 4.850) [Link]

8. Fu-Ying Dao, Hao Lv, Wei Su, Zi-Jie Sun, Qin-Lai Huang, Hao Lin* (2021) iDHS-Deep: An integrated tool for predicting DNase I hypersensitive sites by deep neural network. Briefings in Bioinformatics, 22(5): bbab047. (2020 IF: 11.622) [Link]

7. Hao Lv&, Fu-Ying Dao&, Hasan Zulfiqar, Wei Su, Hui Ding, Li Liu*, Hao Lin* (2021) A sequence-based deep learning approach to predict CTCF-mediated chromatin loop. Briefings in Bioinformatics, 22(5): bbab031. (2020 IF: 11.622) [Link]

6. Fu-Ying Dao, Hao Lv, Dan Zhang, Zi-Mei Zhang, Li Liu*, Hao Lin*. (2021) DeepYY1: a deep learning approach to identify YY1-mediated chromatin loops. Briefings in Bioinformatics, 22(4):bbaa356. (2020 IF: 11.622) [Link] (ESI)

5. Fu-Ying Dao, Hao Lv, Hasan Zulfiqar, Hui Yang, Wei Su, Hui Gao, Hui Ding, Hao Lin*. (2021) A computational platform to identify origins of replication sites in eukaryotes. Briefings in Bioinformatics, 22(2): 1940–1950. (2020 IF: 11.622) [Link] (ESI)

4. Fu-Ying Dao &, Hao Lv &, Yu-He Yang, Hasan Zulfiqar, Hui Gao, Hao Lin*. (2020) Computational identification of N6-Methyladenosine sites in multiple tissues of mammals. Computational and Structural Biotechnology Journal, 18: 1084–1091. (2019 IF: 6.018) [Link]

3. Fu-Ying Dao, Hao Lv, Fang Wang, Chao-Qin Feng, Hui Ding*, Wei Chen*, Hao Lin*. (2019) Identify origin of replication in Sccharomyces cerevisiae using two-step feature selection technique. Bioinformatics, 35(12):2075-2083. (2018 IF: 4.531) [Link] (ESI,Hot)

2. Fu-Ying Dao, Hao Lv, Fang Wang, Hui Ding*. (2018) Recent advances on the machine learning methods in identifying DNA replication origins in eukaryotic genomics. Frontiers in Genetics, 9: 613. (2017 IF: 4.151) [Link]

1. Fu-Ying Dao, Hui Yang, Zhen-Dong Su, Wuritu Yang, Yun Wu, Ding Hui, Wei Chen*, Hua Tang*, Hao Lin*. (2017) Recent advances in conotoxin classification by using machine learning methods. Molecules, 22: 1057. (2016 IF: 2.861) [Link]