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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.

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.

  1. Develop and maintain bioinformatics analysis pipeline for in vitro cancer diagnostic products.
  2. 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.

  1. Perform bioinformatics analysis for NGS data including ChIP-seq, RNA-seq, HiC, and 4C-seq etc.
  2. 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)