Author

M. Palaniappan

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 2

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Assay:metabolomics· 2 Organism:mouse· 2 Research Focus:cell type annotation· 1 Research Focus:cell-cell communication· 1 Approach:experimental assay· 1 Approach:machine learning (classical)· 1 Research Focus:spatial domain detection· 1

Frequent Co-Authors

J. Kim· 2 shared M. M. Matzuk· 2 shared R. Chen· 2 shared A. Botros· 1 shared D. A. Gaul· 1 shared E. Y. Park· 1 shared F. M. Fernandez· 1 shared F. O. Fernandez· 1 shared

Activity by Year

2023-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 33 mutual co-author links

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2 shared papersCancer Biology

J. Kim

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

Ultrahigh Resolution Lipid Mass Spectrometry Imaging of High-Grade Serous Ovarian Cancer Mouse Models

X. Ma, A. Botros, S. R. Yun, E. Y. Park, O. Kim, S. Park, T.-H. Pham, R. Chen, M. Palaniappan, M. M. Matzuk, J. Kim, F. M. Fernandez

This study uses high-resolution MSI to analyze lipid changes in ovarian cancer mouse models, identifying biomarkers for diagnosis.

bioRxiv · Oct 30, 2023Cancer Biology

Machine Learning Reveals Lipidome Remodeling Dynamics in a Mouse Model of Ovarian Cancer

O. O. Bifarin, S. Sah, D. A. Gaul, S. G. Moore, R. Chen, M. Palaniappan, J. Kim, M. M. Matzuk, F. O. Fernandez

This study uses machine learning to analyze lipidome changes in a mouse model of ovarian cancer, identifying early and late-stage lipid alterations associated with cancer progression.

bioRxiv · Jan 4, 2023 · PreprintCancer Biology