Nae-Chyun Chen 陳乃群

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Now

I work on personalized cancer vaccines. We use liquid biopsy to improve how the vaccines are designed.

Before

• Exai Bio · 2022–2026
  Software Engineer to Head of Computational Platform. Led engineering and worked hands-on in bioinformatics and machine learning for a cell-free RNA platform for early cancer detection.
• Google Health · 2020
  Research Intern, DeepVariant team. Led a population-aware DeepVariant model that calls variants more accurately than the default model.
• Johns Hopkins University · 2018–2022
  PhD in Computer Science with Ben Langmead. Improved how we use the human reference genome by addressing assembly errors and lack of genetic diversity.
• National Taiwan University · 2010–2017
  MS in Electronics Engineering: hardware accelerators for sequence alignment. BS in Electrical Engineering and BA in Economics. 台大漁服.

Selected papers

• Improved sequence mapping using a complete reference genome and lift-over.
  Chen et al. Nature Methods (2024)
• Improving variant calling using population data and deep learning.
  Chen et al. BMC Bioinformatics (2023)
• The complete sequence of a human genome.
  Nurk et al. Science (2022)
• Profiling germline adaptive immune receptor repertoire with gAIRR Suite.
  Lin*, Lin*, Chen* et al. Frontiers in Immunology (2022)
• Reference flow: reducing reference bias using multiple population genomes.
  Chen et al. Genome Biology (2021)
• LevioSAM: fast lift-over of variant-aware reference alignments.
  Mun*, Chen*, Langmead. Bioinformatics (2021)

* equal contribution. Full list on Google Scholar.

Software

• levioSAM2 · lift-over of read alignments between references
• reference flow · alignment to multiple population references
• DeepVariant · contributor, population-aware model

Podcast

I co-host 生技來一刻, a Mandarin podcast where we interview people in biotech about science and careers. 100k+ downloads.