Zhaowei Yu

ChromBERT-tools: A versatile toolkit for context-specific embedding of transcription regulators across different cell types

ChromBERT-tools generates context-specific embeddings of transcription regulators for different cell types to enhance regulatory modeling and interpretation.

Learning interpretable representation for context-specific transcription regulatory networks using a foundation model

ChromBERT, a foundation model pre-trained on ChIP-seq data, generates interpretable representations of context-specific transcription regulatory networks and improves imputation and modeling of regulatory effects in cell types.

Decoding the genomic landscape of chromatin-associated biomolecular condensates

The paper introduces CondSigDetector, a computational framework to identify chromatin-associated biomolecular condensates, revealing their genomic landscapes and components in mESC and K562 cells.

PSPire: a machine learning predictor for high-performance screening of phase-separating proteins without intrinsically disordered regions

PSPire is a machine learning predictor that improves identification of phase-separating proteins without intrinsically disordered regions by incorporating residue and structure-level features.