Dr. Shih-Yu Chen is a Associate Research Fellow at the Institute of Biomedical Sciences (IBMS), Academia Sinica, where he has made pioneering contributions to the field of single-cell analysis, immune function, and technology development.
Dr. Chen's research focuses on advancing the detection and quantification of biomolecules at enhanced resolutions and parameters. During his postdoctoral training in Dr. Garry Nolan's lab at Stanford University, he utilized single-cell technologies such as multiplexed imaging and mass cytometry to explore biological diversity and developed innovative tools for revealing cellular details. Among Dr. Chen's recent achievements is his contribution to the development of high-definition multiplex ion beam imaging (HD-MIBI), a technique for multiplexed biomolecular detection at the nanoscale. This technology has provided novel insights into subnuclear territories and drug distribution in situ. His team has also made advances in detecting accessible chromatin using mass cytometry and ion beam imaging, leading to significant findings about genome accessibility and cellular responses.
In the area of immune research, Dr. Chen has explored natural killer (NK) cell heterogeneity through high-dimensional single-cell analysis, shedding light on NK cell function in various clinical contexts. His studies have revealed the impact of NK cell receptor diversity on viral clearance and identified key metabolic and environmental factors influencing NK cell activity. His work on T cell exhaustion has also provided new insights into DNA damage response pathways and their role in immune function and therapy resistance.
Dr. Chen has developed and applied multi-omic approaches to study immune responses in disease states, including cancer and fibrotic diseases. His research has highlighted critical interactions between macrophages and fibroblasts and identified novel immune regulatory mechanisms that could inform therapeutic strategies. In the context of cancer, Dr. Chen's work has been pivotal in identifying biomarkers that can predict patient responses to immunotherapies, including cancer vaccines.
The ability to detect and quantify more types of biomolecules at higher resolutions is crucial for our understanding of biological functions in cells and tissues. For example, single-cell level analyses by fluorescence-based flow cytometry have been a mainstay of immunologic inquiry for nearly four decades. Flow cytometry, which can provide data on ploidy, immuno-phenotype, frequency of cell subsets, expression levels of proteins, and function in single cells, has revolutionized our understanding of cellular individuality in immune function. Our laboratory uses two recently developed technologies, mass cytometry and multiplexed ion beam imaging, which facilitate high dimensional, quantitative analysis of molecules at single-cell resolution to enable a deeper understanding of how the immune system interacts with cancer cells. Better understand the underlying mechanism of the dysregulations of immune cells within tumor microenvironment could potentially lead to the design of therapeutic strategies to enhance or reinvigorate the anti-tumor effector functions.
Single cell analysis
- 2021 Academia Sinica Career Development Award
- 2019-2021 Awards for newly hired exceptional talent from National Science and Technology Council
- 2019-2022 Newly recruited academic research award from Academia Sinica
- 2012-2014 Novo Nordisk STAR Postdoc Fellowship
- 2007-2010 U.C. Davis Pathology Fellowship
- 1999&2001 National Taiwan University President's Award
M.D. National Taiwan University
Ph.D. University of California, Davis
Research Scientist. Stanford University
Job Description
Key Responsibilities:
Assist in conducting single-cell experiments and research activities under the guidance of senior researchers.
Perform both wet lab (e.g., cell culture, flow cytometry, RNA sequencing) and dry lab (e.g., data processing, statistical analysis, computational modeling) tasks.
Collect, analyze, and interpret data from single-cell studies.
Maintain accurate records of experiments and findings.
Conduct literature reviews to support ongoing research.
Participate in lab meetings, discussions, and presentations.
Benefits:
Hands-on experience in cutting-edge single-cell research projects.
Exposure to both experimental and computational methodologies.
Opportunity to work with leading experts in the field.
Potential for co-authorship on publications.
Preferred Intern Education Level
Currently enrolled in or recently completed a degree in [relevant field, e.g., Biology, Bioinformatics, Computational Biology, Engineering, etc.].
Skill sets or Qualities
Qualifications:
Strong analytical and problem-solving skills.
Experience with both wet lab techniques (e.g., pipetting, PCR, cell sorting) and dry lab tools (e.g., Python, R, MATLAB for bioinformatics).
Ability to work independently as well as part of a team.
Excellent communication and organizational skills.
Prior research experience in single-cell analysis is a plus but not required.