Siyuan Zhang

The paper maps gene-by-gene-by-environment epistasis in cancer metastasis using CRISPR perturbations in mice, showing niche-dependent fitness and transcriptome convergence.

This study identifies tumor-intrinsic IFNγ signaling and niche adaptation as key drivers of early colonization in ovarian cancer metastasis using MetTag, a single-cell barcoding approach.

This study shows that a single chromosome 3p break initiates ccRCC evolution by creating a fitness bottleneck that selects for recurrent aneuploidies.

PAIR combines CRISPR activation and RNA knockdown to study bidirectional gene interactions in DNA repair, revealing strategies to enhance CRISPR-based gene editing precision.

This study introduces ReMiTT, a computational method to identify T cell migration trails in spatial transcriptomics data, revealing chemokine trends and enriched pathways associated with T cell movement in tumors.

This study uses a hybrid in vivo model to show that the aged extracellular matrix promotes breast cancer progression, with LOX identified as a key driver.

This study develops site-specific antibody-gas vesicle conjugates as durable cancer-targeting ultrasound contrast agents, validated through testing on cancer cell lines and tumor-bearing mouse cells.

The paper develops an eigen-image based method for detecting microbubbles and gas vesicles in ultrasound imaging, improving signal-to-noise ratio and localization accuracy.

The paper introduces a Bayesian framework to map cell-cell interactions from spatial transcriptomics data, revealing new biological insights in cancer and immune responses.

The paper develops a CNN-based denoising method for mixed Poisson-Gaussian noise in fluorescence microscopy images, achieving real-time performance and superior SNR improvement.

This paper introduces instant FLIM, a real-time fluorescence lifetime imaging method, and demonstrates its application in long-term in vivo brain imaging in zebrafish and mice.