Author

Ruikun He

Chinese Academy of SciencesORCID 0000-0002-2292-8884Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:deep learning· 3 Research Focus:gene regulatory network inference· 3 Research Focus:differential expression· 2 Assay:scRNA-seq· 2 Research Focus:benchmarking· 1 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Approach:contrastive learning· 1

Frequent Co-Authors

Yixue LiiD· 3 shared Junwei LiuiD· 2 shared Chao MaiD· 1 shared Chenxin YiiD· 1 shared Feng‐ao WangiD· 1 shared Jiajun CheniD· 1 shared Junxiang DingiD· 1 shared Lijian HuiiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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3 shared papersBioinformatics

Yixue LiORCID

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3 papers

Recent·Most cited

Exploring phenotype-related single-cells through attention-enhanced representation learning

Qinhua Wu, Junxiang Ding, Ruikun He, Lijian Hui, Junwei Liu, Yixue Li

This study introduces a method to predict clinical phenotypes from single-cell data using attention-based multiple instance learning, demonstrating its effectiveness in predicting disease severity and age-related phenotypes.

Genome Medicine · Jan 21, 2026Peer-reviewedBioinformatics

scTFBridge: A Disentangled Deep Generative Model Informed by TF-Motif Binding for Gene Regulation Inference in Single-Cell Multi-Omics

Feng‐ao Wang, Chenxin Yi, Jiajun Chen, Ruikun He, Junwei Liu, Yixue Li

scTFBridge infers gene regulatory networks from single-cell multi-omics data by integrating TF-motif binding knowledge, outperforming baselines in cis- and trans-regulation tasks.

Nature Communications · Oct 15, 2025Peer-reviewedBioinformatics

Knowledge Graph-based Thought: a knowledge graph enhanced LLMs framework for pan-cancer question answering

Yichun Feng, Lu Zhou, Chao Ma, Yikai Zheng, Ruikun He, Yixue Li

The paper introduces a framework that combines large language models with knowledge graphs to improve factual accuracy in biomedical question answering, demonstrating effectiveness in drug repositioning and resistance prediction.

GigaScience · Oct 2, 2024Peer-reviewedBioinformatics