collaborators

6 papers

cs.LG2026

scLLM-DSC: LLM-Knowledge Enhanced Cross-Modal Deep Structural Clustering for Single-Cell RNA Sequencing

Ping Xu, Pengjiang Li, Tian Du +6

Clustering is fundamental to scRNA-seq analysis, serving as a cornerstone for identifying cell populations and resolving tissue heterogeneity. However, existing methods focus on mi…

cs.DB2026

A Comprehensive Survey on Vector Database: Storage and Retrieval Technique, Challenge

Le Ma, Ran Zhang, Yikun Han +17

As high-dimensional vector data increasingly surpasses the processing capabilities of traditional database management systems, Vector Databases (VDBs) have emerged and become tight…

q-bio.GN2025

scCluBench: Comprehensive Benchmarking of Clustering Algorithms for Single-Cell RNA Sequencing

Ping Xu, Zaitian Wang, Zhirui Wang +5

Cell clustering is crucial for uncovering cellular heterogeneity in single-cell RNA sequencing (scRNA-seq) data by identifying cell types and marker genes. Despite its importance,…

q-bio.GN2025

scUnified: An AI-Ready Standardized Resource for Single-Cell RNA Sequencing Analysis

Ping Xu, Zaitian Wang, Zhirui Wang +7

Single-cell RNA sequencing (scRNA-seq) technology enables systematic delineation of cellular states and interactions, providing crucial insights into cellular heterogeneity. Buildi…

cs.CL2025

SciTopic: Enhancing Topic Discovery in Scientific Literature through Advanced LLM

Pengjiang Li, Zaitian Wang, Xinhao Zhang +4

Topic discovery in scientific literature provides valuable insights for researchers to identify emerging trends and explore new avenues for investigation, facilitating easier scien…

q-bio.GN2025

scSiameseClu: A Siamese Clustering Framework for Interpreting single-cell RNA Sequencing Data

Ping Xu, Zhiyuan Ning, Pengjiang Li +5

Single-cell RNA sequencing (scRNA-seq) reveals cell heterogeneity, with cell clustering playing a key role in identifying cell types and marker genes. Recent advances, especially g…