Author

Xinke Zhan

Macao Polytechnic UniversityORCID 0000-0002-1235-3220Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Assay:protein sequence· 2 Research Focus:benchmarking· 1 Research Focus:gene regulatory network inference· 1 Research Focus:protein design· 1 Research Focus:protein structure prediction· 1 Approach:statistical model· 1

Frequent Co-Authors

Shaolong Lin· 2 shared Shirley W. I. SiuiD· 2 shared Silong ZhaiiD· 2 shared Tiantao Liu· 2 shared Bingwen ZhuiD· 1 shared Huanxiang LiuiD· 1 shared Junwen DengiD· 1 shared Tao Bi· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 24 mutual co-author links

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2 shared papersBioinformatics

Shaolong Lin

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJul 10, 2026

MAERM: Predicting Enzyme-Reaction Matching Relationships with a Mixed-Attention Model

Tiantao Liu, Silong Zhai, Shaolong Lin…·Shirley W. I. Siu

MAERM predicts enzyme-reaction matching relationships using a mixed-attention model, outperforming baselines and enabling enzyme design.

DOI 10.64898/2026.07.06.736902

protein sequencedeep learning

𝕏 PostBluesky

BioinformaticsbioRxivPreprintJan 13, 2026

Protein-peptide Interaction Representation Learning with Pretrained Language Models

Xinke Zhan, Silong Zhai, Tiantao Liu…·Shirley W. I. Siu

PepInter is a deep learning framework that uses pre-trained language models to predict protein-peptide interactions and bioactivity, outperforming existing methods on benchmark datasets.

1 citation

protein sequencedeep learning

𝕏 PostBluesky