Author

Jiaxiong Lu

Baylor College of Medicine

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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Bioengineering· 1 Genetic & Genomic Medicine· 1 Molecular Biology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Research Focus:GWAS / association mapping· 2 Organism:human· 2 Research Focus:cell-cell communication· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:experimental assay· 1 Research Focus:fine-mapping· 1

Frequent Co-Authors

Rui CheniD· 3 shared Aboozar MonavarfeshaniiD· 1 shared Alexander E. DavisiD· 1 shared Berenice Sarahi Cortez· 1 shared Cheng‐Hui LiniD· 1 shared Degui ZhiiD· 1 shared Fabian Joachim TheisiD· 1 shared Han CheniD· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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3 shared papersBioengineering

Rui ChenORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Monitoring Gene Expression in Retina with Synthetic Serum Markers

Jiaxiong Lu, Sangsin Lee, Meng Wang, Karen Zheng, Soo Hwan Oh, Jocelyn Lee, Sujung Soh, Yexuan Cao, Xuan Bao, Yifan Huang, Shirin Nouraein, Zigang Wu, Jerzy O. Szablowski, Rui Chen

This study uses synthetic serum markers (RMAs) to monitor retinal gene expression and cell survival through blood tests, showing high sensitivity and non-destructiveness.

bioRxiv · Jan 16, 2026 · PreprintBioengineering

Integrated multi-omics single cell atlas of the human retina

Jin Li, Jun Wang, Ignacio L. Ibarra, Xuesen Cheng, Malte D. Luecken, Jiaxiong Lu, Aboozar Monavarfeshani, Wenjun Yan, Yiqiao Zheng, Zhen C. Zuo, Samantha Lynn Zayas Colborn, Berenice Sarahi Cortez, Leah A. Owen, Nicholas M. Tran, Karthik Shekhar, , Rui Chen

The paper creates a comprehensive human retina cell atlas using single-cell multi-omics data, revealing over 110 cell types and their gene regulatory networks, and enables fine-mapping of GWAS and eQTL variants.

bioRxiv · Nov 7, 2023 · PreprintMolecular Biology

iGWAS: image-based genome-wide association of self-supervised deep phenotyping of human medical images

Ziqian Xie, Tao Zhang, Sangbae Kim, Jiaxiong Lu, Wanheng Zhang, Cheng‐Hui Lin, Man-Ru Wu, Alexander E. Davis, Roomasa Channa, Luca Giancardo, Han Chen, Sui Wang, Rui Chen, Degui Zhi

The paper introduces iGWAS, a method using self-supervised deep learning to extract phenotypes from medical images for GWAS, finding new genetic loci related to retinal vessel development.

medRxiv · May 26, 2022 · PreprintGenetic & Genomic Medicine