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Author

Mengmeng Wei

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Book Open access Aug 2026

Multi-Hop Diffusion-Wavelet Semantic Learning for Zero-Shot Circrna-Mirna Interaction Prediction

This paper proposes BioWave, a multi-hop diffusion-wavelet model that learns both structural and semantic representations for accurate CMI prediction and achieves superior performance compared to state-of-the-art baselines, particularly in zero-shot settings.

Mengmeng Wei, Lei Wang, Peng-Wei Hu et al. · 0 citations
Book Open access Aug 2026

MuSeL: A Multi-Scale Adaptive Graph Representation Learning Framework for Microbe-Drug Association Prediction

MuSeL is proposed, a multi-scale adaptive graph representation learning framework that jointly mitigates the above issues from two complementary perspectives: global topology modeling and local structure optimization.

Yuehu Wu, Lei Wang, Zhengwei Li et al. · 0 citations
Open access Aug 2026

NARVGA: A Hybrid Framework Integrating Matrix Factorisation and Adversarial Graph Learning for circRNA-Disease Association Prediction

A computer-based method that combines several types of biological information to predict likely relationships between circular ribonucleic acids and diseases is developed and shows a strong ability to distinguish known associations from unconfirmed ones.

Mianshuo Lu, Mengmeng Wei, Changchun Liu et al. · 0 citations
Jul 2026

Functionally Guided Graph Learning for Robust Cross-Patient Cell-Type Annotation in Single-Cell RNA Sequencing

Experiments on three cross-patient scRNA-seq data sets demonstrate that PathoGraph achieves stable annotation performance across 32 directed reference-to-query transfer tasks, showing competitive and stable performance compared with representative marker-based, correlation-based, and model-based annotation methods.

Yue C. Li, Mengmeng Wei, Xinfei Wang et al. · 0 citations
Book Open access Aug 2026

MuSeL: A Multi-Scale Adaptive Graph Representation Learning Framework for Microbe-Drug Association Prediction

MuSeL is proposed, a multi-scale adaptive graph representation learning framework that jointly mitigates the above issues from two complementary perspectives: global topology modeling and local structure optimization.

Yuehu Wu, Lei Wang, Zhengwei Li et al. · 0 citations

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