18 citations · 50 across the 25 of their papers we have counts for
5 papers · 1 filter
Enhanced Gene Selection in Single-Cell Genomics: Pre-Filtering Synergy and Reinforced Optimization
Weiliang Zhang, Zhen Meng, Dongjie Wang +4
Recent advancements in single-cell genomics necessitate precision in gene panel selection to interpret complex biological data effectively. Those methods aim to streamline the anal…
Enhancing Tabular Data Optimization with a Flexible Graph-based Reinforced Exploration Strategy
Xiaohan Huang, Dongjie Wang, Zhiyuan Ning +6
Tabular data optimization methods aim to automatically find an optimal feature transformation process that generates high-value features and improves the performance of downstream…
FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization
Zhiyuan Ning, Chunlin Tian, Meng Xiao +5
Federated Learning faces significant challenges in statistical and system heterogeneity, along with high energy consumption, necessitating efficient client selection strategies. Tr…
scCDCG: Efficient Deep Structural Clustering for single-cell RNA-seq via Deep Cut-informed Graph Embedding
Ping Xu, Zhiyuan Ning, Meng Xiao +4
Single-cell RNA sequencing (scRNA-seq) is essential for unraveling cellular heterogeneity and diversity, offering invaluable insights for bioinformatics advancements. Despite its p…
scInterpreter: Training Large Language Models to Interpret scRNA-seq Data for Cell Type Annotation
Cong Li, Meng Xiao, Pengfei Wang +3
Despite the inherent limitations of existing Large Language Models in directly reading and interpreting single-cell omics data, they demonstrate significant potential and flexibili…