Author

Haiping Lu

University of SheffieldORCID 0000-0002-0349-2181Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Research Focus:benchmarking· 3 Research Focus:clustering· 3 Approach:machine learning (classical)· 2 Approach:statistical model· 2 Assay:bulk RNA-seq· 1 Research Focus:cell-cell communication· 1 Assay:CITE-seq· 1 Approach:deep learning· 1

Frequent Co-Authors

Shuo ZhouiD· 2 shared Alexandra I. Herghelegiu· 1 shared Allan LawrieiD· 1 shared Chia-Hao ChengiD· 1 shared Christopher J. RhodesiD· 1 shared Christopher Richard CoxiD· 1 shared Dennis Y.Q. WangiD· 1 shared Gaolang GongiD· 1 shared

Activity by Year

2019-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 8 mutual co-author links

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2 shared papersNeuroscience

Shuo ZhouORCID

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Author profile →

5 papers

Recent·Most cited

Global and cross-omics feature aggregation improves single-cell multi-omics integration and clustering

Yingjie Guo, Chia-Hao Cheng, Zheqing Zhu, Jin Zhou, Haiping Lu, Yuhua Qian, Zhen Liang

scCODI improves single-cell multi-omics integration and clustering by aggregating cross-omics features and using contrastive learning, outperforming existing methods across nine datasets.

bioRxiv · Apr 10, 2025 · PreprintBioinformatics

Omada: Robust clustering of transcriptomes through multiple testing

Sokratis Kariotis, Pei Fang Tan, Haiping Lu, Christopher J. Rhodes, Martin R. Wilkins, Allan Lawrie, Dennis Y.Q. Wang

Omada automates transcriptomic clustering by integrating machine learning, improving accessibility and robustness across diverse RNA expression datasets.

GigaScience · Jan 1, 2024Peer-reviewedBioinformatics

APRILE: Exploring the Molecular Mechanisms of Drug Side Effects with Explainable Graph Neural Networks

Hao Xu, Shengqi Sang, Herbert Yao, Alexandra I. Herghelegiu, Haiping Lu, James T. Yurkovich, Laurence Yang

APRILE uses explainable graph neural networks to identify molecular mechanisms of polypharmacy side effects, generating explanations for over 900,000 side effect-drug pairs.

bioRxiv · Jul 2, 2021 · PreprintBioinformatics

Improving multi-site autism classification based on site-dependence minimisation and second-order functional connectivity

Mwiza Kunda, Shuo Zhou, Gaolang Gong, Haiping Lu

This paper improves multi-site autism classification by minimizing site dependence using second-order functional connectivity features, achieving 73% accuracy on the ABIDE dataset.

bioRxiv · Feb 1, 2020 · PreprintNeuroscience

Improving Whole-Brain Neural Decoding of fMRI with Domain Adaptation

Shuo Zhou, Christopher Richard Cox, Haiping Lu

This paper improves whole-brain fMRI neural decoding using domain adaptation, achieving an 8.94% accuracy improvement by leveraging pre-existing source data.

Lecture notes in computer science · Jan 1, 2019Peer-reviewedNeuroscience