Author

Yuanye Chi

The Jackson Laboratory for Genomic MedicineORCID 0009-0001-2139-8172Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Biochemistry· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Assay:metabolomics· 3 Research Focus:benchmarking· 2 Research Focus:database / resource· 2 Organism:human· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1

Frequent Co-Authors

Joshua M. MitchelliD· 3 shared Maheshwor ThapaiD· 3 shared Shuzhao LiiD· 3 shared Shujian Zheng· 2 shared Aleksandr Alekseevich SmirnoviD· 1 shared Jianguo XiaiD· 1 shared Liang LiiD· 1 shared Xiuxia DuiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 35 mutual co-author links

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3 shared papersBiochemistry

Joshua M. MitchellORCID

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3 papers

Recent·Most cited

Assessing the metabolomics "dark matter" by a detectable khipu model

Yuanye Chi, Joshua M. Mitchell, Shujian Zheng, Maheshwor Thapa, Shuzhao Li

The paper analyzes metabolomics 'dark matter' using a detectable khipu model, showing most abundant features have identifiable ion patterns, while many remain unknown.

Metabolomics · May 24, 2026Peer-reviewedBiochemistry

Constructing a consensus serum metabolome

Yuanye Chi, Joshua M. Mitchell, Maheshwor Thapa, Shujian Zheng, Zackary Frohock, Liang Li, Aleksandr Alekseevich Smirnov, Xiuxia Du, Shuzhao Li

The paper constructs a consensus serum metabolome from over 100,000 mass spectrometry acquisitions, revealing gaps in current databases and improving LC-MS metabolomics annotation.

bioRxiv · May 7, 2025 · PreprintBiochemistry

Common data models to streamline metabolomics processing and annotation, and implementation in a Python pipeline

Joshua M. Mitchell, Yuanye Chi, Maheshwor Thapa, Zhiqiang Pang, Jianguo Xia, Shuzhao Li

The paper introduces a Python pipeline and data structures for metabolomics data processing, annotation, and standardization, demonstrating its utility with large-scale datasets.

PLoS Computational Biology · Jun 6, 2024Peer-reviewedBioinformatics