Author

Xiaojun Li

Johns Hopkins UniversityORCID 0000-0001-7345-2364Unclaimed ORCID profile · follow to get notified of new preprints

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Xiaojun Li2 papers · Johns Hopkins University

Biology Disciplines

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Developmental Biology· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Approach:experimental assay· 2 Organism:mouse· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:cell type annotation· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Angelika DoetzlhoferiD· 2 shared Alex Porter· 1 shared Charles MorganiD· 1 shared Elena Chrysostomou· 1 shared Lin LiiD· 1 shared Paul KearneyiD· 1 shared Peter J. MazzoneiD· 1 shared Stephen W. Hunsucker· 1 shared

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2017-2025 · peak 1/yr

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10 top collaborators · 20 mutual co-author links

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2 shared papersDevelopmental Biology

Angelika DoetzlhoferORCID

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3 papers

Recent·Most cited

Developmental BiologyNature CommunicationsPeer-reviewedSep 1, 2025

The Notch ligand Jagged1 plays a dual role in cochlear hair cell regeneration.

Xiaojun Li, Charles Morgan, Lin Li…·Angelika Doetzlhofer

This study shows that Jagged1/Notch signaling maintains cochlear supporting cell progenitor-like characteristics and metabolic genes, and its inhibition enhances hair cell regeneration.

13 citationstop 1%

mousebulk RNA-seq

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Developmental BiologyProceedings of the National Academy of SciencesPeer-reviewedAug 21, 2020

LIN28B controls the regenerative capacity of neonatal murine auditory supporting cells through activation of mTOR signaling

Xiaojun Li, Angelika Doetzlhofer

This study shows that LIN28B maintains supporting cell plasticity in the cochlea by activating mTOR signaling, enabling hair cell regeneration in immature mice.

60 citations

mouseexperimental assay

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BioinformaticsPLoS ONEPeer-reviewedMay 17, 2017

An Integrated Risk Predictor for Pulmonary Nodules

Paul Kearney, Stephen W. Hunsucker, Xiaojun Li…·Peter J. Mazzone

This paper develops an integrated risk predictor for lung nodules combining clinical factors and proteomic markers, finding that the combination outperforms either alone.

16 citations

humanproteomics

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