Author

Jun Yan

University of CalgaryORCID 0000-0002-7141-4687Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Jun Yan6 papers · China Agricultural University

Biology Disciplines

Click to filter author papers

Bioinformatics· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 2 Approach:statistical model· 2 Approach:benchmark study· 1 Research Focus:differential expression· 1 Assay:DNA methylation· 1 Research Focus:drug response / drug discovery· 1 Assay:electronic health records· 1 Research Focus:fine-mapping· 1

Frequent Co-Authors

Qing LiiD· 2 shared Quan LongiD· 2 shared Wanqing WeniD· 2 shared Wei ZhengiD· 2 shared Xiao‐Ou ShuiD· 2 shared Xingyi GuoiD· 2 shared Zhishan CheniD· 2 shared Adetunji T. ToriolaiD· 1 shared

Activity by Year

2023-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

2 shared papersGenetic & Genomic Medicine

Qing LiORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Large-scale integration of omics and electronic health records to identify potential risk protein biomarkers and therapeutic drugs for cancer prevention

Qing Li, Qingyuan Song, Zhishan Chen, Jung-Yoon Choi, Victor Rau Moreno, Jie Ping, Wanqing Wen, Chao Li, Xiang Shu, Jun Yan, Xiao‐Ou Shu, Qiuyin Cai, Jirong Long, Jeroen R. Huyghe, Rish K. Pai, , Xingyi Guo

This study integrates large-scale omics and electronic health records to identify risk proteins and drugs for cancer prevention, finding 101 novel proteins and three drugs associated with reduced colorectal cancer risk.

The American Journal of Human Genetics · Dec 2, 2025Peer-reviewedGenetic & Genomic Medicine

Tissue-specific transfer-learning enables retasking of a general comprehensive model to a specific domain

Qing Li, Deshan Perera, Zhishan Chen, Wanqing Wen, Dinghao Wang, Jun Yan, Xiao‐Ou Shu, Wei Zheng, Xingyi Guo, Quan Long

The paper applies transfer learning to adapt a general-purpose model to a specific domain using limited data, demonstrating improved performance in breast cancer-related tasks.

bioRxiv · Sep 11, 2023 · PreprintBioinformatics