Collection
Quantitative Methods to Decipher Cellular Heterogeneity — from single‑cell to spatial omic methods
Here we invite submissions to a collection of articles focusing on the quantitative methods to decipher cellular heterogeneity.
Single-cell and spatial omic technologies are transforming our ability to interrogate intercellular heterogeneity in complex tissues, organs, and tumors. New methodological innovations in experimental methods, algorithms, statistical methods, and software are being developed to decipher temporal and spatial dynamics of cellular diferentiation, cell–cell interactions, pattern formation of complex organs, clonal evolution of cancer cells, and host-microbe interactions.
Editors
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Professor Joshua W. K. Ho
Professor Joshua W. K. Ho is affiliated to the School of Biomedical Sciences, Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
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Professor Xi Chen
Professor Xi Chen is at the Laboratory of Data Discovery for Health Limited (D24H), Hong Kong Science Park, Hong Kong SAR, China
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Professor Mu He
Professor Mu He is at the Department of Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
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Professor Yuanhua Huang
Profrssor Yuanhua Huang is affiliated to the School of Biomedical Sciences and the Department of Statistics and Actuarial Science at the University of Hong Kong (HKU), Hong Kong, China
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Professor Jessica C. Mar
Professor Jessica C. Mar is affiliated to the Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, Australia
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Professor David J. H. Shih
Professor David J. H. Shih is affiliated to the School of Biomedical Sciences at the Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong, China
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Professor Angela R. Wu
Professor Angela R. Wu is affiliated to the Division of Life Science, and Division of Biomedical Engineering, The Hong Kong University of Science and Technology, HongKong, China
