Author

Xingsi Xie

Peking University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:database / resource· 1 Approach:deep learning· 1 Organism:fungi (other)· 1 Research Focus:gene regulatory network inference· 1 Research Focus:software / tool· 1 Research Focus:variant calling· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Aili FaniD· 1 shared Dong LiuiD· 1 shared Liangren ZhangiD· 1 shared Wenhan LiniD· 1 shared Yiran ZhouiD· 1 shared Zequan HuangiD· 1 shared Zhenming LiuiD· 1 shared

Activity by Year

2025-2025 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 21 mutual co-author links

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1 shared paperBioinformatics

Aili FanORCID

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1 paper

Recent·Most cited

f-BGM enables fungi-specific genome mining in high accuracy and interpretability

Yiran Zhou, Dong Liu, Zequan Huang, Xingsi Xie, Wenhan Lin, Liangren Zhang, Aili Fan, Zhenming Liu

f-BGM is a deep learning framework for fungal genome mining that outperforms existing methods in BGC detection and provides interpretability for enzyme identification and domain partnerships.

bioRxiv · Jul 8, 2025 · PreprintBioinformatics