Cencan Xing

OmicOS provides an agent-operable omics ecosystem that enables AI systems to execute and verify analyses using community methods, achieving high performance in benchmark tasks.

OmicClaw provides a natural-language framework for reproducible multi-omics analysis using the OmicVerse ecosystem, improving performance over baseline models in complex workflows.

This paper introduces an inducible Cas9 system for tissue- and stage-specific gene editing in zebrafish and mouse embryos, demonstrating its effectiveness in inducing mutations in target genes.

CellOntologyMapper standardizes cell type annotations by mapping user-defined names to standardized ontological terms, improving data integration and analysis across diverse single-cell datasets.

This study shows BMP-Smad1/9 signaling is essential for zebrafish PGC proliferation and survival but not for their fate or migration.

This paper introduces GlioME, a patient-derived glioma organoid model that retains the tumor microenvironment, showing high responsiveness to chemotherapy and accurately predicting patient response to vebreltinib.

FT-Kernel predicts cell fate factors and dynamics along pseudotime using cell-state density and regression weights, outperforming existing methods in capturing lineage transitions and interactions.

OmicVerse integrates bulk and single-cell RNA-seq analysis with a pipeline that restores continuity in interrupted single-cell data using Beta-Variational AutoEncoder and graph neural networks.

This paper introduces scLTNN, a method for automatically inferring origin and end cell states and developmental trajectories from scRNA-seq data with low computational cost.