Zhaolei Zhang

Recruitment of the m6A/Am demethylase FTO to target RNAs by the telomeric zinc finger protein ZBTB48

This study identifies ZBTB48 as a regulator of FTO's substrate selectivity by facilitating its binding to m6A/m6Am-containing RNAs, affecting RNA decay and cancer cell growth.

Deciphering 3'UTR mediated gene regulation using interpretable deep representation learning

This paper introduces 3UTRBERT, a Transformer-based model for analyzing 3UTR sequences, achieving better performance in predicting RBP binding, m6A sites, and RNA localization.

Modeling Single Cell Trajectory Using Forward-Backward Stochastic Differential Equations

This paper introduces a forward-backward stochastic differential equations (FBSDE) model to infer single-cell developmental trajectories, showing improved accuracy over existing methods on scRNA-seq datasets.

RNANetMotif: identifying sequence-structure RNA network motifs in RNA-protein binding sites

RNANetMotif identifies sequence-structure RNA network motifs in RNA-protein binding sites using graph theory and validates them with molecular dynamics simulations.

Postnatal developmental trajectory of sex-biased gene expression in the mouse pituitary gland

This study profiles gene and miRNA expression in mouse pituitaries across postnatal ages to identify sex-biased gene regulation and cell-type proportion differences during development.

SARS-CoV-2 Nucleocapsid protein attenuates stress granule formation and alters gene expression via direct interaction with host mRNAs

This study identifies SARS-CoV-2 N protein interactions with host proteins and mRNAs, showing it attenuates stress granule formation and alters gene expression.

Functional characterization of RebL1 highlights the evolutionary conservation of oncogenic activities of the RBBP4/7 orthologue in Tetrahymena thermophila

The paper identifies RebL1 as an orthologue of human RBBP4/7 in Tetrahymena thermophila, showing its role in epigenetic regulation and oncogenic functions across species.

LncRNA and predictive model to improve the diagnosis of clinically diagnosed pulmonary tuberculosis

The paper identifies three lncRNAs and develops a nomogram model to improve diagnosis of pulmonary tuberculosis in patients without microbiologic evidence.