Publications

Selected Publications

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Genome Research · 2026

Reference-informed spatial domain detection using weak supervision for spatial transcriptomics

Ma, X., Jin, W., Lu, Q., et al.

A weakly supervised framework that borrows annotated reference tissue to detect spatial domains in new spatial transcriptomics samples.

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Nature Communications · 2025

Spatial mapping of the brain metabolome, lipidome and glycome

Clarke, H.A.^†, Ma, X.^†, Shedlock, C.J.^†, et al.

Metabolites, lipids and glycans resolved from a single tissue section and assembled into one spatial multi-omics atlas of the brain.

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Nature Metabolism · 2025

AI-driven framework to map the brain metabolome in three dimensions

Ma, X.^†, Shedlock, C.J.^†, Medina, T.^†, et al.

A deep learning pipeline that reconstructs the brain metabolome in three dimensions from serial mass spectrometry imaging sections.

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Bioinformatics · 2024

Deep5hmC: predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model

Ma, X., Thela, S.R., Zhao, F., et al.

A multimodal deep learning model that predicts genome-wide 5hmC modification by combining DNA sequence with matched epigenetic data.

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Peer-Reviewed Publications

^† indicates co-first author.

1. Ma, X., Allison, D., Macedo, J.K.A., et al. Machine learning-based prediction of clinical outcomes in glioblastoma using glycomics features. Computational and Structural Biotechnology Journal (2026).
2. Ma, X., Jin, W., Lu, Q., et al. Reference-Informed Detection of Spatial Domains Using Weak Supervision for Spatial Transcriptomics. Genome Research (2026).
3. Hawkinson, T.R., Liu, Z., Ribas, R.A., et al., Ma, X., et al. Hyperglycosylation is a metabolic driver of Alzheimer's disease. Nature Metabolism (2026).
4. Ribas, R., Tang, Q., Caffee, S., et al., Ma, X., Chen, L., Sun, R., et al. Mass Spectrometry-based Spatial Imaging of the Cochlea. Journal of the American Society for Mass Spectrometry (2026).
5. Clarke, H.A.^†, Ma, X.^†, Shedlock, C.J.^†, et al. Spatial mapping of the brain metabolome lipidome and glycome. Nature Communications, 16, 4373 (2025).
6. Ma, X.^†, Shedlock, C.J.^†, Medina, T.^†, et al. AI-driven framework to map the brain metabolome in three dimensions. Nature Metabolism (2025).
7. Clarke, H.A., Hawkinson, T.R., Clarke, H., et al., Ma, X., et al. Glycogen drives tumour initiation and progression in lung adenocarcinoma. Nature Metabolism (2025).
8. Ma, X., Thela, S.R., Zhao, F., et al. Deep5hmC: predicting genome-wide 5-hydroxymethylcytosine landscape via a multimodal deep learning model. Bioinformatics, 40(9), btae528 (2024).
9. Zhao, F., Ma, X., Yao, B., et al. Scada: A novel statistical method for differential analysis of single-cell chromatin accessibility sequencing data. PLOS Computational Biology, 20(8) (2024).

Manuscripts Under Revision

1. Rodriguez-Palma, E., Gomez, K., Calderon-Rivera, A., et al., Ma, X., et al. A peptidomimetic inhibitor of moesin alleviates chronic pain by suppressing NaV1.7 and NaV1.8 channels. Science Translational Medicine (under revision).
2. Guarnieri, J.W., Maghsoudi, Z., Kim, J., et al., Ma, X., et al. Guardians of the Mitochondria: Space Mitochondria 2.0 Systemic Analysis Reveals Bioenergetic Dysregulation Across Species. Cell (under revision).

Manuscripts Under Review

1. Jin, W., Zhao, F., Ma, X., et al. DeepCNet: An interpretable deep learning model for inferring cell type-specific promoter-enhancer interactions from single-cell multiome data. Nature Communications (under review).
2. Liu, Z.^†, Ma, X.^†, Ribas, R., et al. Metabolic Coherence of the Mouse Brain. Cell (under review).
3. Medina, T., Quiñones, S., Liu, Z., et al., Ma, X., et al. A multi-organ spatial metabolomic atlas of exercising mice reveals neuronal Complex I as a convergent and sufficient axis for tau pathology reduction in PS19. Science (under review).