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Chan Zhou PhD

TitleAssistant Professor
InstitutionUMass Chan Medical School
DepartmentPopulation and Quantitative Health Sciences
AddressUMass Chan Medical School
368 Plantation Street AS9-1079
Worcester MA 01605
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    Other Positions
    InstitutionT.H. Chan School of Medicine
    DepartmentPopulation and Quantitative Health Sciences
    DivisionBiostatistics And Health Services Research

    InstitutionMorningside Graduate School of Biomedical Sciences
    DepartmentMasters in Clinical Investigation

    InstitutionMorningside Graduate School of Biomedical Sciences
    DepartmentPopulation Health Sciences

    InstitutionMorningside Graduate School of Biomedical Sciences
    DepartmentSystems Computational and Quantitative Biology

    Collapse Biography 
    Collapse education and training
    Zhejiang University, Hangzhou, , ChinaBSMathematics/Applied Mathematic
    Mass General Hospital & Harvard Medical School, Boston, MAPostdocRNA epigenomics
    Zhejiang University, Hangzhou, , ChinaPHDBioinformatics
    Zhejiang Univeristy, Hangzhou, ChinaPhDBioinformatics
    Fudan University , Shanghai, ChinaVisiting PhD studentBioinformatics
    University of Georgia, Athens, GA, USA Visiting PhD studentComputational Biology
    Zhejiang Univeristy, Hangzhou, ChinaBSMathematics and Applied Mathematics

    Collapse Overview 
    Collapse overview


    We develop novel computational methods and pipelines for analyzing large-scale high throughput data to understand noncoding RNA epigenomics in genetics and disease toward advancing precision medicine. Please see more in our group website: http://chanzhoulab.org/

    Join our team! 

    We are looking for creative and passionate people including:

    ·       Postdoctoral Associate
    ·       Graduate students
    ·       Visiting PhD students/Scholar
    We are computational biologists and bioinformatics scientists. Aim to understand genomics, epigenomics, noncoding RNAs and gene regulation from basic sciences towards precision medicine of human disease through computational and big data-driven approaches. We entail the development of new computational algorithms, statistical/quantitative methods, and combining cutting-edge bioinformatics technologies to process various types/platforms of sequencing data (including second and third generation sequencing and single cell sequencing data) to make biomedical discoveries.
    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 3 referee).
    • Ph.D in computational biology, bioinformatics, computer science, applied 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 high-throughput sequencing 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-/co-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.
    Graduate student: MD/PhD students in the Graduate School of Medical Sciences of UMass Medical school (UMMS) can rotate in the Zhou Lab starting Spring, 2020. Prospective PhD students can join the Program of Bioinformatics and Integrative Biology in UMMS Graduate School of Medical Sciences. Please email Chan to learn more. Include a CV and research interests.
    Visiting PhD students/scholar: We are excited to host visiting graduate students/scholar for research experiences at UMass Medical School. Please email Chan with a CV and research interests

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    Collapse Bibliographic 
    Collapse selected publications
    Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.
    Newest   |   Oldest   |   Most Cited   |   Most Discussed   |   Timeline   |   Field Summary   |   Plain Text
    PMC Citations indicate the number of times the publication was cited by articles in PubMed Central, and the Altmetric score represents citations in news articles and social media. (Note that publications are often cited in additional ways that are not shown here.) Fields are based on how the National Library of Medicine (NLM) classifies the publication's journal and might not represent the specific topic of the publication. Translation tags are based on the publication type and the MeSH terms NLM assigns to the publication. Some publications (especially newer ones and publications not in PubMed) might not yet be assigned Field or Translation tags.) Click a Field or Translation tag to filter the publications.
    1. Sun C, Zhou C, Daneshvar K, Ben Saad A, Kratkiewicz AJ, Toles BJ, Arghiani N, Hess A, Chen JY, Pondick JV, York SR, Li W, Moran S, Gentile S, Ur Rahman R, Li Z, Zhou P, Sparks R, Habboub T, Kim BM, Choi MY, Affo S, Schwabe RF, Popov YV, Mullen AC. Conserved long noncoding RNA TILAM promotes liver fibrosis through interaction with PML in hepatic stellate cells. Hepatology. 2024 Apr 02. PMID: 38563629.
    2. Li Z, Zhou P, Kwon E, Fitzgerald KA, Weng Z, Zhou C. Flnc: Machine Learning Improves the Identification of Novel Long Noncoding RNAs from Stand-Alone RNA-Seq Data. Noncoding RNA. 2022 Oct 13; 8(5). PMID: 36287122.
    Co-Authors (4)
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