Bin Zhu

This study identifies subtype-specific mutational mechanisms and links them to host metabolic factors in endometrial cancer using genomic and transcriptomic data from 440 tumors.

This study analyzes 1024 lung adenocarcinomas to identify evolutionary patterns and mutational mechanisms, revealing distinct trajectories linked to smoking, ancestry, and retrotransposition.

SUITOR selects the optimal number of mutational signatures using cross-validation, improving accuracy over existing methods in cancer genomics.

The paper presents whole-genome and whole-exome sequencing datasets from a multi-center, cross-platform study to benchmark NGS technologies and bioinformatics pipelines in cancer genomics.

The paper establishes reference samples with high-coverage whole-genome sequencing to create truth sets for somatic mutation and germline variant detection using NGS technologies.

This study evaluates reproducibility and accuracy of cancer mutation detection using whole-genome and whole-exome sequencing across multiple sequencing centers and bioinformatics pipelines.

This study examines intratumor heterogeneity and clonal evolution in papillary renal cell carcinomas using whole-genome sequencing and DNA methylation data, revealing distinct patterns of genomic and epigenomic evolution across subtypes.

This study quantifies genetic and epigenetic intratumor heterogeneity in lung adenocarcinoma and links it to poor prognosis.

The paper identifies three immune subtypes in luminal breast cancer through immune gene expression profiling and links them to distinct genomic and clinical features.

hsegHMM is a hidden Markov model for allele-specific copy number analysis that addresses hypersegmentation, outperforming FACETS in uneven coverage scenarios.