Author

Jixin Liu

Shandong UniversityORCID 0000-0001-8414-4199Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

Click to filter author papers

Signature Assays, Organisms & Methods

Click to filter · or open tag

Assay:spatial transcriptomics· 3 Research Focus:cell-cell communication· 2 Approach:graph neural network· 2 Organism:human· 2 Research Focus:spatial domain detection· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1

Frequent Co-Authors

Bingqiang LiuiD· 3 shared Anjun MaiD· 2 shared Dong He XuiD· 2 shared Qin MaiD· 2 shared Zihai LiiD· 2 shared Carter AlleniD· 1 shared Dan H. BarouchiD· 1 shared Dongjun ChungiD· 1 shared

Activity by Year

2022-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 39 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

3 shared papersBioinformatics

Bingqiang LiuORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJul 2, 2026

SpaGRD deciphers signaling architectures in spatial transcriptomics using graph reaction-diffusion systems

Jixin Liu, Shuli Sun, Zhitong Chen…·Bingqiang Liu

SpaGRD models cell-cell communication using graph reaction-diffusion systems, revealing spatially resolved signaling patterns in spatial transcriptomics data.

DOI 10.64898/2026.06.28.735031

spatial transcriptomicsgraph neural network

𝕏 PostBluesky

BioinformaticsbioRxivPreprintDec 10, 2022

Spatial omics representation and functional tissue module inference using graph Fourier transform

Yuzhou Chang, Jixin Liu, Anjun Ma…·Qin Ma

This paper introduces SpaGFT, a graph Fourier transform model for spatial omics data analysis, enabling accurate identification of tissue modules and their functional relationships in spatial transcriptomics and proteomics data.

4 citations

mousehuman

𝕏 PostBluesky

BioinformaticsComputational and Structural Biotechnology JournalPeer-reviewedJan 1, 2022

Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning

Yuzhou Chang, Fei He, Juexin Wang…·Qin Ma

RESEPT uses deep learning to visualize and characterize tissue architecture from spatial transcriptomics data, revealing pathological structures in Alzheimer's and glioblastoma samples.

56 citationstop 5%

humanspatial transcriptomics

𝕏 PostBluesky