Research:
We develop innovative computational methods, machine learning architectures, and scalable pipelines to decode the genomic "dark matter"—specifically non-canonical DNA and RNA variants driving human diseases. By integrating multi-omics data, our lab bridges the gap between molecular mechanisms and precision clinical translation.
- AI-Driven Multi-Omics Modeling: We design deep learning algorithms to predict and reveal the role of non-canonical DNA and RNA variants, including lncRNAs, circRNAs, gene fusions, and epi-transcriptomic modifications, as well as to elucidate how DNA variants (such as SNPs and CNVs) disrupt these regulatory networks.
- Scalable Multi-Platform Tools: We build end-to-end computational workflows for bulk and single-cell multi-omic profiling, chromatin dynamics, and long-read sequencing to harmonize data from large-scale population health biobanks.
- Translational Disease-associated Variant Discovery: We leverage multi-omics molecular data with clinical informatics to discover novel diagnostic biomarkers and therapeutic targets.
Current Lab member:
Euijin Kwon (Graduate student 2021 – Present)
Lina Yan (Postdoc 2026 – Present)
Former Lab member:
Zixiu Li (Postdoc 2020 – 2026)
Peng Zhou (Graduate student 2020 – 2025)
TienChan Hsieh (Clinical Fellow 2022 – 2025)
Lab News:
March, 2026: Welcome Lina to the lab as a new postdoctoral associate.
December 2025: Congratulations to Billy on passing his PhD dissertation defense.
Join our team! We are looking for creative and passionate Postdoctoral Candidate:
The lab member will benefit from collaboration with world-class biologists and physicians from UMass and Harvard medical area, MIT and other prestigious institutes. To ensure the success of career development of our lab member, Dr. Zhou will tailor Lab member’ trainings to meet the career goals of individual lab member.
Pls email Chan Zhou : chan DOT zhou AT umassmed.edu to learn more
Postdoctoral Associate: Please email Chan with your cover letter (including research interests) and CV (including a list of publication, computational skills, and a list of at least 2 referee).
REQUIRED QUALIFICATIONS:
- Ph.D in computational biology, bioinformatics, computer science, mathematics, statistics, biophysics, engineering, biological sciences or related field. Ph.D candidates anticipating thesis defense are encouraged to apply for hire after completion of Ph.D.
- Experience in method development and/or analysis of single-cell or long-red seq data is preferred.
- Working knowledge of molecular biology and sequencing technologies
- Proficiency with Unix/Linux shell and at least one of the following programming languages: C, C++, Python, Perl or R.
- Excellent communication and writing skills
- Previous record of independent research with first-/corresponding- author publications.
- Able to work both independently and in teams
- Excellent teamwork and time management with the ability to meet deadlines and multi-task across multiple research projects.