Bin Zhu

TRACER navigates rearrangement-driven sesterterpene chemical space via multimodal enzyme-product representation learning

TRACER predicts terpene skeletal rearrangements by learning enzyme-product associations, identifying novel carbon skeletons and mechanistic insights.

Spatial Total RNA Sequencing of Formalin-Fixed Paraffin Embedded Tissues by spRandom-seq

This paper introduces spRandom-seq, a spatial RNA sequencing method for FFPE tissues, which captures both host and microbial RNAs with higher efficiency than oligo(dT)-based methods.

Revisiting the diversity of secondary endosymbionts in the major pest oat aphid, Rhopalosiphum padi

This study investigates the presence of secondary endosymbionts in Rhopalosiphum padi, finding limited diversity beyond Hamiltonella defensa and highlighting potential technical and ecological factors affecting detection.

HPV co-infection burden, vaginal microbiota restructuring, and host context are associated with Cervical precancer risk in a racially restricted observational cohort

The paper assesses how HPV burden, vaginal microbiota, and host factors predict CIN3 risk in a racially diverse cohort, finding that integrated models outperform HPV-only models.

Revealing the Drivers Underlying Distinct Evolutionary Trajectories in Lung Adenocarcinoma

This study identifies three distinct evolutionary trajectories in lung adenocarcinomas using whole-genome sequencing, revealing that some never-smoking tumors follow smoking-like paths driven by KRAS mutations.

Identifying High-Dimensional Genomic Factors Modulating Biological Networks Across Multi-Omics Data

GFBioNet identifies genomic factors modulating trait-trait relationships in multi-omics data, revealing host genetics, microbial taxa, and mutations affecting biological networks.

A Gm6AG-binding protein from Vibrio cholerae.

The paper identifies a novel 6mA-binding protein from Vibrio cholerae that recognizes the G6mAG motif, differing from DpnI's G6mATC specificity.

A benchmarking study of copy number variation inference methods using single-cell RNA-sequencing data

This study benchmarks five scCNV inference methods across multiple scRNA-seq platforms and mixed samples, finding variations in performance based on data characteristics and batch effects.

MEGSA: A powerful and flexible framework for analyzing mutual exclusivity of tumor mutations

The paper introduces MEGSA, a framework for analyzing mutual exclusivity of tumor mutations, identifying novel gene sets and associations in cancer types like AML and breast cancer.