1 citations · 4 across the 4 of their papers we have counts for
5 papers
DPCformer: An Interpretable Deep Learning Model for Genomic Prediction in Crops
Pengcheng Deng, Kening Liu, Mengxi Zhou +5
Genomic Selection (GS) uses whole-genome information to predict crop phenotypes and accelerate breeding. Traditional GS methods, however, struggle with prediction accuracy for comp…
DeepPlantCRE: A Transformer-CNN Hybrid Framework for Plant Gene Expression Modeling and Cross-Species Generalization
Yingjun Wu, Jingyun Huang, Liang Ming +3
The investigation of plant transcriptional regulation constitutes a fundamental basis for crop breeding, where cis-regulatory elements (CREs), as the key factor determining gene ex…
Deep Learning and Explainable AI: New Pathways to Genetic Insights
Chenyu Wang, Chaoying Zuo, Zihan Su +4
Deep learning-based AI models have been extensively applied in genomics, achieving remarkable success across diverse applications. As these models gain prominence, there exists an…
Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy
Ruizhan Xue, Huimin Deng, Fang He +2
With the extensive application of Graph Neural Networks (GNNs) across various domains, their trustworthiness has emerged as a focal point of research. Some existing studies have sh…
Verbalized Graph Representation Learning: A Fully Interpretable Graph Model Based on Large Language Models Throughout the Entire Process
Xingyu Ji, Jiale Liu, Lu Li +2
Representation learning on text-attributed graphs (TAGs) has attracted significant interest due to its wide-ranging real-world applications, particularly through Graph Neural Netwo…