Author

Can Liu

Suzhou University of Science and TechnologyORCID 0000-0001-5451-4144Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Neuroscience· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Approach:experimental assay· 1 Research Focus:gene regulatory network inference· 1 Organism:mouse· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Brooke C. JarvieiD· 1 shared Haiguang LiuiD· 1 shared Hao HeiD· 1 shared Nikolaos ChatzirisiD· 1 shared Zachary A. KnightiD· 1 shared

Activity by Year

2020-2026 · peak 1/yr

Co-Author Collaboration Network

5 top collaborators · 4 mutual co-author links

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1 shared paperNeuroscience

Brooke C. JarvieORCID

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2 papers

Recent·Most cited

NeurosciencebioRxivPreprintJan 6, 2026

An orthogonal TRAP enables intersectional genetic access to activated neurons in the mouse brain

Nikolaos Chatziris, Brooke C. Jarvie, Can Liu, Zachary A. Knight

The paper introduces X-TRAP, an orthogonal genetic tool for activity-dependent labeling of neurons in mice, enabling intersectional analysis of neural circuits involved in food intake.

DOI 10.64898/2025.11.30.691330

mouseexperimental assay

𝕏 PostBluesky

BioinformaticsiSciencePeer-reviewedFeb 12, 2020

Model reconstruction from Small angle X-ray Scattering data using deep learning methods

Hao He, Can Liu, Haiguang Liu

The paper presents a deep learning algorithm using an auto-encoder to reconstruct 3D protein models from SAXS data, demonstrating accuracy without prior size information.

49 citations

deep learningvariational autoencoder

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