School of Science Division of Life Science 39 The Application of BIG DATA Technologies in Precision Cancer Medicine Supervisor: WANG Jiguang / LIFS Student: XIE Zequan / BCB Course: UROP 1100, Fall UROP 2100, Spring Estimating cellular composition within complex tissues is both challenging and essential in biomedical research. We here introduce Deconv-DAN, a deep learning deconvolution framework that utilizes single cell proteomic profiles to resolve cellular composition with high accuracy. In this pipeline, an unbiased mix-up strategy first generates diverse pseudo-bulk training samples from the reference data. A deep adaptation network is then trained to ensure that the neural network can effectively generalize to target bulk samples. Comprehensive benchmarking across multiple in silico and in vitro tasks demonstrates Deconv-DAN’s accuracy and robustness, underscoring its utility for deconvolution of bulk proteomics and DNA methylation samples. The Application of BIG DATA Technologies in Precision Cancer Medicine Supervisor: WANG Jiguang / LIFS Student: ZHANG Huixian / BCB Course: UROP 1100, Summer Teratomas model human development through differentiation into ectoderm, mesoderm, and endoderm lineages. We reanalyzed single-cell RNA sequencing data from four teratomas to resolve germ layer contributions. Integrated analysis (Seurat v4) identified 20 transcriptionally distinct clusters. Germ layer assignment via established marker genes revealed: 6 ectodermal, 3 endodermal, and 10 mesodermal clusters, with 1 clusters unresolved. Automated cell typing (ACT platform) corroborated manual annotations in 13/20 clusters (65% concordance), while marker expression resolved 6 additional clusters. Unassigned clusters (9) suggest transitional or novel states. This work establishes a cellular atlas of teratoma differentiation, validating scRNA-seq for pluripotency assessment while highlighting limitations in progenitor cell annotation. How Cells Safeguard Mitochondria, the Powerhouse of the Cell? Supervisor: WANG Lan / LIFS Student: LEE Juwon / BCB Course: UROP 1100, Summer This project focuses on the purification and structural analysis of plant ATAD3 homologs (ATAD3A1 and ATAD3B2), essential mitochondrial proteins involved in mitochondrial DNA organization, mitochondrial morphology, mitochondrial function, and survival of the organism. By creating specific constructs, culturing cells, optimizing expression conditions in Expi293 cells, and screening various detergents for effective protein extraction, we aim to obtain properly folded proteins that are correctly targeted to the mitochondria for further analysis. These findings provide a solid foundation for further large scale purification and structural studies of plant ATAD3, advancing our understanding of its role in mitochondrial bioenergetics, fitness, function, and stress responses.
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