most citedGraph Neural Networks for Multimodal Single-Cell Data Integration

78 citations · 142 across the 6 of their papers we have counts for

collaborators

6 papers

cs.IR2023★ 10 cited

Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation

Wei Jin, Haitao Mao, Zheng Li +17

Modeling customer shopping intentions is a crucial task for e-commerce, as it directly impacts user experience and engagement. Thus, accurately understanding customer preferences i…

cs.LG2023★ 20 cited

Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs

Zhikai Chen, Haitao Mao, Hang Li +8

Learning on Graphs has attracted immense attention due to its wide real-world applications. The most popular pipeline for learning on graphs with textual node attributes primarily…

q-bio.GN2023★ 21 cited

Single-Cell Multimodal Prediction via Transformers

Wenzhuo Tang, Hongzhi Wen, Renming Liu +5

The recent development of multimodal single-cell technology has made the possibility of acquiring multiple omics data from individual cells, thereby enabling a deeper understanding…

q-bio.GN2023★ 10 cited

Single Cells Are Spatial Tokens: Transformers for Spatial Transcriptomic Data Imputation

Hongzhi Wen, Wenzhuo Tang, Wei Jin +7

Spatially resolved transcriptomics brings exciting breakthroughs to single-cell analysis by providing physical locations along with gene expression. However, as a cost of the extre…

q-bio.QM2022★ 3 cited

Deep Learning in Single-Cell Analysis

Dylan Molho, Jiayuan Ding, Zhaoheng Li +12

Single-cell technologies are revolutionizing the entire field of biology. The large volumes of data generated by single-cell technologies are high-dimensional, sparse, heterogeneou…

cs.LG2022★ 78 cited

Graph Neural Networks for Multimodal Single-Cell Data Integration

Hongzhi Wen, Jiayuan Ding, Wei Jin +3

Recent advances in multimodal single-cell technologies have enabled simultaneous acquisitions of multiple omics data from the same cell, providing deeper insights into cellular sta…