I am a dedicated and innovative researcher with a significant background in computational biology, bioinformatics, and alternative proteins, particularly in the realm of cell-cultivated meat. My academic and professional pursuits have helped me contribute to both plant cell research and the cell-cultivated meat industry. At the Department of Food Science in University Park, PA, I engage deeply in the scRNA data analysis of plant cells, utilizing advanced molecular dynamic tools including Gromacs and Amber as well as GNN,GTN and CNN deep learning models to uncover novel proteins and predict protein/peptide properties.
I am currently a Ph.D. student at PSU, mentored by Yi Zhang. I got my B.Eng.from Jiangsu University of Science and Technology in Food Engineering. Throughout my studies, I spent several years doing internships and gaining experience in industry, including biotechs and cultured meat companies.
Bioinformatics
My experience encompasses a vast array of omics data analysis, including genomics, transcriptomics, proteomics, and single-cell RNA sequencing (scRNA-seq). Utilizing tools like Scanpy and seurat, I have adeptly extracted, analyzed, and interpreted complex biological data. Specifically, through scRNA-seq data analysis, I identified critical targets essential for the development of serum-free media in cell-cultivated meat production.
Computational Biology
My research is deeply entrenched in plant cell transcriptomics, with a primary focus on identifying alternative proteins, reminiscent of Rubisco. I possess a robust foundation in utilizing molecular dynamics tools, notably QM/MM like Gromacs and Amber, to explore the complexities of enzymatic products and gauge their consequential impacts. Additionally, I specialize in the application of deep learning, especially graph neural networks, for discerning protein-protein interactions and mechanisms.
Looking forward to any academic networking and feel free to contact me!
Most recent publications on Google Scholar.
‡ indicates equal contribution.
Recent progress in magnetic nanoparticles and mesoporous materials for enzyme immobilization: an update
Ding Saisai, Zhu J.P., Wang Y., Yu Y., Zhao Z.
Brazilian Journal of Biology, 82. 2021.
Immobilization of the extracellular recombinant Lucky9 xylanase from *Bacillus subtilis* enhances activity at high temperature and pH
Ding Saisai, Zhu J.P., Wang Y., Wu B., Zhao Z.
FEBS Open bio, 10(12), pp.2733-2739. 2020.
The insecticidal activity of methyl benzoate against *Tribolium castaneum* by transcriptomic analysis and in-silico simulation
Wang L., Ding Saisai, Zhang N.J., Lu Y., Geng X., Zhao Z.
Journal of Stored Products Research, 97, p.101972. 2022.
Recent progress in magnetic nanoparticles and mesoporous materials for enzyme immobilization: an update
Ding Saisai, Zhu J.P., Wang Y., Yu Y., Zhao Z.
Brazilian Journal of Biology, 82. 2021.
Immobilization of the extracellular recombinant Lucky9 xylanase from *Bacillus subtilis* enhances activity at high temperature and pH
Ding Saisai, Zhu J.P., Wang Y., Wu B., Zhao Z.
FEBS Open bio, 10(12), pp.2733-2739. 2020.
The insecticidal activity of methyl benzoate against *Tribolium castaneum* by transcriptomic analysis and in-silico simulation
Wang L., Ding Saisai, Zhang N.J., Lu Y., Geng X., Zhao Z.
Journal of Stored Products Research, 97, p.101972. 2022.
A segmentation method for adipocyte progenitor cells based on SUnet algorithm
Zhou Guanghong, Ding Saisai, Ding Shijie, Wu Zhongyuan, Li Jiamin, Tang Changbo.
Jiangsu Province: CN114998360A, 2022-09-02.
A method for predicting the concentration of serum-free medium components
Zhou Guanghong, Ding Saisai, Ding Shijie, Wu Zhongyuan, Li Jiamin, Tang Changbo.
Jiangsu Province: CN115101118A, 2022-09-23.
Full Resume in PDF.
This website was built with jekyll based on the template from Martin Saveski!