Zhiliang Bai

This study enhances CAR-T cell migration through synthetic cytokine receptors, reducing metastasis in TNBC mouse models.

StarTrak infers cellular migration and phylogeny by integrating somatic variants, spatial data, and transcriptomics at single-pixel resolution in spatial genomics.

REDCAT maps single-cell type-specific metabolic activities in tissues using multimodal all-optical imaging, revealing metabolic specialization and reprogramming in immune and liver tissues.

The paper uses single-cell foundation models to predict durable CAR T response from pre-infusion scRNA-seq data, achieving high accuracy without requiring perfect cell annotation.

The paper identifies yeast-derived lipids that extend lifespan in Drosophila by remodeling metabolism in the gut and brain, enhancing tissue homeostasis and communication.

This study maps age-related cellular senescence in human lymph nodes, identifying senescence markers and spatial shifts in germinal center B cells.

SuperFocus integrates histopathology with single-cell spatial multi-omics data from spot-based measurements, improving accuracy by 28-73% over existing methods.

Thermostable RNaseH release of barcoded cDNA keeps sections intact for CODEX imaging, yielding same-section whole-transcriptome and protein maps plus CODEX-guided spot deconvolution in FFPE tissues.

The paper introduces SuMMIT-SRS, a multiplexed metabolic imaging technique, and demonstrates its application in various cell types to study metabolic rewiring.

ASTRO is an automated pipeline for spatial transcriptomics analysis, optimized for FFPE samples and capable of detecting coding and non-coding RNAs.

Perturb-DBiT co-sequences spatial transcriptomes and gRNAs on one tissue section, supporting genome-wide in vivo CRISPR screens in FFPE and fresh-frozen tumors across three cancer models.

This paper introduces Patho-DBiT, a method for spatial transcriptomics in FFPE tissues, enabling RNA biology analysis including splicing, variants, and regulatory networks in clinical samples.

This paper presents spatial epigenome profiling using CUT&Tag and microfluidic barcoding to map histone modifications at tissue scale and single-cell level in mouse embryos and olfactory bulbs.

DBiT-seq enables high-spatial-resolution multi-omics mapping of mouse embryos by deterministic barcoding, revealing tissue types and fine features like retinal pigmented epithelium and microvasculature.

The paper was withdrawn due to a duplicate posting and directs readers to the current version on bioRxiv.