Feng Cui

The paper identifies four nucleosomal DNA classes and shows their association with TF binding, revealing DNA-encoded codes for nucleosome positioning and interaction modes.

This study uses machine learning on RNA-seq data to identify sex-specific gene panels for bladder cancer biomarkers, achieving high accuracy in distinguishing cancer from non-tumor samples.

This study develops a computational pipeline to analyze ChIP-seq and RNA-seq data, revealing locus-specific p53 regulation of transposable elements in normal and cancer cells.

The paper investigates how histone N-tails influence nucleosome positioning by comparing tailless and wild-type nucleosomes on human BRCA1 DNA.

This paper introduces a deep learning framework for gene network inference that integrates gene expression and interactions, achieving more accurate predictions than existing methods.

The paper identifies an anti-WW/SS nucleosomal sequence pattern enriched in mammalian genes and shows its correlation with RNA Pol II transcription and chromatin remodeling.

BioVR is a VR platform for visualizing biological data, demonstrating integration of protein sequences and structures in a 3D environment.

The paper identifies distinct chromatin contexts for p53 binding sites in normal and cancer cells, revealing differences in histone marks, DNA methylation, and nucleosome occupancy.