Yi Zhang
@yi-zhang-compbio.bsky.social
Assistant Professor@Duke #compbio #machinelearning #genomics👩🔬 💻 Alumni UIUC/DFCI/Harvard. https://yi-zhang-compbio-lab.github.io/ Recruiting postdoc!
- Locally: identification of multi-cellular neighborhoods and cell-cell interactions, where gene expression mediating cell-cell communications are further revealed. E.g. Various immune hubs enriching different T-myeloid interactions; TLS structure seen in other tumor samples. 7/
February 14, 2025 at 9:42 PM
- Locally: identification of multi-cellular neighborhoods and cell-cell interactions, where gene expression mediating cell-cell communications are further revealed. E.g. Various immune hubs enriching different T-myeloid interactions; TLS structure seen in other tumor samples. 7/
The STHD cell labels enable many analyses- globally: segmentation of tissue structures and detection of cell type-specific differential genes/pathways. e.g. The inside tumor nodule expresses higher epithelial-specific stem genes, and higher macrophage-specific SPP1+ state. 6/
February 14, 2025 at 9:42 PM
The STHD cell labels enable many analyses- globally: segmentation of tissue structures and detection of cell type-specific differential genes/pathways. e.g. The inside tumor nodule expresses higher epithelial-specific stem genes, and higher macrophage-specific SPP1+ state. 6/
STHD enables scalable spatial inference and interactive exploration of cellular niches and immune hubs, facilitating genome-wide and cell type-specific spatial comparisons. One example full-size colon cancer VisiumHD generated by STHDviewer is at yi-zhang-compbio-lab.github.io/STHDviewer_c.... 5/
February 14, 2025 at 9:42 PM
STHD enables scalable spatial inference and interactive exploration of cellular niches and immune hubs, facilitating genome-wide and cell type-specific spatial comparisons. One example full-size colon cancer VisiumHD generated by STHDviewer is at yi-zhang-compbio-lab.github.io/STHDviewer_c.... 5/
We show that STHD accurately infers cell type identities at subcellular level and guides cell type-specific binning, achieving high performance in benchmarks and preserving cell type-specific expression. Below is a small "tumor bagel" patch (~0.25%) from one colon cancer VisiumHD 4/
February 14, 2025 at 9:42 PM
We show that STHD accurately infers cell type identities at subcellular level and guides cell type-specific binning, achieving high performance in benchmarks and preserving cell type-specific expression. Below is a small "tumor bagel" patch (~0.25%) from one colon cancer VisiumHD 4/
In details, STHD uses machine learning to model high-resolution spots with neighbor regularization, where the loss function addresses sparsity by modeling count statistics, incorporating neighbor similarities, and leveraging reference single-cell RNA-seq data. 3/
February 14, 2025 at 9:42 PM
In details, STHD uses machine learning to model high-resolution spots with neighbor regularization, where the loss function addresses sparsity by modeling count statistics, incorporating neighbor similarities, and leveraging reference single-cell RNA-seq data. 3/