Investigating large-scale, deep and interpretable single-cell morpho-physical profiling of immune cells

Professor Tsia, Kevin Kin Man   (Principal Investigator (PI))

Professor Chan Godfrey Chi Fung   (Co-Investigator)

36

2022-01-01

1125732

Investigating large-scale, deep and interpretable single-cell morpho-physical profiling of immune cells

Biophysical phenotyping, Imaging flow cytometry, Single-cell analysis

Biomedical Engineering,Photonics

Biology and Medicine (M)

17125121

General Research Fund (GRF)

2021

On-going

1 1. Formulate an integrative, deep-learning single-cell morpho-physical profiling strategy – We will establish an ultralarge-scale (>millions cells) and deep-learning-driven single-cell profiling strategy that automatically learns the quantitative morphological and biophysical (or called morpho-physical) features from the multi-contrast single-cell images. Using deep learning and other advanced bioinformatic tool developed in our group, we aim to gain biologically relevant interpretation of these latent single-cell morpho-physical profiles. 2 2. Characterize single-cell morpho-physical profiles of immune cells – We aim to generate the systematic knowledge base of single-cell morpho-physical profiles for different immune cell types (major types of leukocytes) and establish their correlations to standard cell-surface markers in different sub-populations at single-cell level. 3 3. Explore the potential of ultralarge-scale and deep single-cell biophysical phenotyping – We will apply our single-cell morpho-physical phenotyping strategy to investigate the heterogeneity of different immune cell types/lineages, in the context of tracking T-cell differentiation, and monitoring minimal residual disease treatment, especially when coupled with the biomolecular analysis at single-cell level.