Author

F. M. Fernandez

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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Bioengineering· 2 Biochemistry· 1 Cancer Biology· 1

Signature Assays, Organisms & Methods

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Assay:metabolomics· 4 Research Focus:cell type annotation· 3 Research Focus:differential expression· 2 Approach:experimental assay· 2 Organism:human· 2 Research Focus:cell-cell communication· 1 Approach:machine learning (classical)· 1 Organism:mouse· 1

Frequent Co-Authors

D. Huang· 2 shared A. A. Nikitina· 1 shared A. Botros· 1 shared A. O. A. Michael· 1 shared A. S. Edison· 1 shared A. Van Grouw· 1 shared C. A. Watson· 1 shared C. K. Asef· 1 shared

Activity by Year

2021-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 10 mutual co-author links

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2 shared papersBioengineering

D. Huang

Mutual co-authors in cluster

Author profile →

4 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

Mass spectrometry imaging reveals early metabolic priming of cell lineage in differentiating human induced pluripotent stem cells

A. A. Nikitina, A. Van Grouw, T. Roysam, D. Huang, F. M. Fernandez, M. L. Kemp

The paper uses mass spectrometry imaging to identify metabolic markers of lineage specification in differentiating human iPSCs, showing phospholipids as early indicators of pluripotency loss.

bioRxiv · Aug 16, 2022Bioengineering

CCS Predictor 2.0: An Open-Source Jupyter Notebook Tool for Filtering Out False Positives in Metabolomics

M. A. Rainey, C. A. Watson, C. K. Asef, M. R. Foster, E. Baker, F. M. Fernandez

CCSP 2.0 predicts collision cross section values for metabolites using machine learning, improving accuracy and alignment with FAIR data principles.

bioRxiv · Aug 9, 2022Biochemistry

Multi-omics characterization of mesenchymal stem/stromal cells for the identification of putative critical quality attributes

T. S. Maughon, X. Shen, D. Huang, A. O. A. Michael, W. A. Shockey, S. H. Andrews, J. M. McRae, M. O. Platt, F. M. Fernandez, A. S. Edison, S. L. Stice, R. A. Marklein

This paper identifies putative critical quality attributes (CQAs) for mesenchymal stem/stromal cells (MSCs) using multi-omics data and PLSR modeling to predict functional capacity.

bioRxiv · May 10, 2021 · PreprintBioengineering