Author

Tianma Xu

Washington University in St. LouisORCID 0000-0002-9969-8976Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 2 Organism:human· 2 Assay:multiome· 2 Approach:deep learning· 1 Research Focus:differential expression· 1 Approach:graph neural network· 1

Frequent Co-Authors

Dekang Cao· 2 shared Emily Chen· 2 shared Fuhai LiiD· 2 shared Guangfu LiiD· 2 shared Michael A. ProvinceiD· 2 shared Philip PayneiD· 2 shared Ben Dizdar· 1 shared Di HuangiD· 1 shared

Activity by Year

2024-2024 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 42 mutual co-author links

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2 shared papersBioinformatics

Dekang Cao

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2 papers

Recent·Most cited

mosGraphFlow: a novel integrative graph AI model mining disease targets from multi-omic data

Heming Zhang, Dekang Cao, Tianma Xu, Emily Chen, Guangfu Li, Yixin Chen, Philip Payne, Michael A. Province, Fuhai Li

This study introduces mosGraphFlow, a graph AI model for analyzing multi-omic data to identify AD-associated biomarkers and signaling pathways, achieving high classification accuracy.

bioRxiv · Aug 1, 2024 · PreprintBioinformatics

mosGraphGPT: a foundation model for multi-omic signaling graphs using generative AI

Heming Zhang, Di Huang, Emily Chen, Dekang Cao, Tianma Xu, Ben Dizdar, Guangfu Li, Yixin Chen, Philip Payne, Michael A. Province, Fuhai Li

mosGraphGPT is a foundation model for multi-omic signaling graphs trained on cancer data and fine-tuned for Alzheimer's Disease, improving classification accuracy and interpretability.

bioRxiv · Aug 1, 2024 · PreprintBioinformatics