Xiang 'Anthony' Chen

The paper identifies non-coding somatic variants in TAL1 regulatory regions that reactivate enhancers normally active in hematopoietic stem cells in T-lineage acute lymphoblastic leukemia.

CanID is a machine learning classifier for pediatric cancer subtypes using RNAseq data, achieving 99% accuracy for solid tumors and 92-93% for hematologic malignancies.

This study shows that targeting RBM39 with indisulam promotes natural killer cell activity and eradicates neuroblastoma regardless of cellular state plasticity.

Seq2Karyotype (S2K) enables in-silico karyotyping from whole-genome sequencing data, revealing intratumoral heterogeneity and evolutionary trajectories in cancer samples.

This study shows that directional myelin growth in zebrafish is driven by a Wnt4b gradient and is essential for proper axon function and behavior.

The paper identifies 'pliancy genes' in Muller glia that enable rapid response to retinal stress, injury, and disease, showing species-specific differences in their activation between zebrafish and mammals.

This study creates two mouse models with conditional c-MYC activation in specific cell types, leading to distinct neuroendocrine tumors resembling human neuroblastoma and somatostatinoma.

This study identifies mafba as a regulator of nrl-independent rod genesis in zebrafish and reveals a bipotent rod/green-cone precursor cell fate decision controlled by nrl.

This paper introduces PTA, a new WGA method that improves variant calling accuracy in single cells, enabling studies of genetic diversity and CRISPR off-target effects.

MethylationToActivity infers promoter activity from DNA methylation data in tumors, showing high accuracy across multiple cancer types.

LCA identifies subtle cell population diversity in large-scale single-cell RNA-seq data using a dual-space model with spectral clustering and technical variation control.

The paper studies the chromatin structure of rod photoreceptors in mice using Hi-C and machine learning to identify regulatory elements involved in retinal development.

The paper identifies differentially methylated regions in myeloid differentiation, showing genetic and developmental influences on methylome dynamics.

VCF2CNA detects copy-number alterations from VCF data with high accuracy and platform independence, outperforming existing methods in neuroblastoma samples.