About this blog
This is my personal blog. I intend to document some of my own
thinking, coding tips, and knowledge roadmap related to python, R,
emacs, bioinformatics, and machine learning.
About me
I am a bioinformatics scientist with a background of human genomics,
epigenetics, cancer biology, and machine learning.
You can know more about me at LinkedIn.
![my photo](/assets/Cai-YiChao.jpg)
Skills and interests
- Bioinformatics
- Python
- R (Bioconductor/Tidyverse/ggplot)
- PyTorch
- Pandas/Numpy
- Linux/Bash
- Git
- Snakemake/nextflow/airflow
- Docker/Singularity
- HPC/SGE
- C++
- SQL
Working experience
-
Senior Bioinformatics Scientist, Illumina AI Lab, Singapore.
Develop and apply deep-learning methods on RNA-seq data to better
understand RNA biology.
- Bioinformatics Scientist, Vela Diagnostics, Singapore.
- Develop and maintain bioinformatics analysis pipeline for in
vitro cancer diagnostic products.
- Acted as a go-to resource for addressing bioinformatics
pipeline queries, providing support to both the internal
business development department and external customers.
- Research Fellow, Cancer Science Institute of Singapore, Singapore.
- Perform bioinformatics analysis for NGS data including
ChIP-seq, RNA-seq, HiC, and 4C-seq etc.
- Data visualization and manuscript writing.
Education
- PhD in Bioinformatics, Department of Biological Science, National
University of Singapore, Singapore.
- Undergraduate student, Bachelor of Engineering, Bioinformation
Technology, Huazhong University of Science and Technology.
Publications
- Cai, Y.*, Zhang, Y.*, Loh, Y. P., Tng, J. Q., Lim, M. C., Cao, Z., Raju, A., Lieberman Aiden, E., Li, S., Manikandan, L., Tergaonkar, V., Tucker-Kellogg, G., & Fullwood, M. J. (2021). H3K27me3-rich genomic regions can function as silencers to repress gene expression via chromatin interactions. Nature communications, 12(1), 719. https://doi.org/10.1038/s41467-021-20940-y
- Cao, F.*, Zhang, Y.*, Cai, Y.*, Animesh, S., Zhang, Y., Akincilar, S. C., Loh, Y. P., Li, X., Chng, W. J., Tergaonkar, V., Kwoh, C. K., & Fullwood, M. J. (2021). Chromatin interaction neural network (ChINN): a machine learning-based method for predicting chromatin interactions from DNA sequences. Genome biology, 22(1), 226. https://doi.org/10.1186/s13059-021-02453-5
- Zhang, Y*., Cai, Y*., Roca, X., Kwoh, C. K., & Fullwood, M. J. (2021). Chromatin loop anchors predict transcript and exon usage. Briefings in Bioinformatics, 22(6), bbab254.
(*co-first authors)