Lei Liu

From Black Box to Biological Insight: AttentioFuse Unlocks Multi-Omics Dynamics in Lung Cancer

AttentioFuse is an interpretable deep learning framework for multi-omics integration in lung cancer that matches state-of-the-art performance and uncovers biological insights.

Uncovering Latent Biological Function Associations through Gene Set Embeddings

This study uses gene set embeddings to uncover biological function associations across species by integrating node2vec with MSigDB data.

Optimization and redevelopment of single-cell data analysis workflow based on deep generative models

The paper improves scRNA-seq analysis by using deep generative models to identify and remove noise cells, enhancing clustering and gene analysis consistency.

Attention-based deep multiple instances learning for classifying circular RNA and other long non-coding RNA

The paper introduces an attention-based deep multiple instance learning model for circRNA identification from lncRNA, showing improved performance and identifying key sequence motifs.

Single-cell transcriptome profiling simulation reveals the impact of sequencing parameters and algorithms on clustering

This study simulates scRNA-seq data to evaluate how sequencing parameters and clustering algorithms affect cell clustering accuracy.