Author

Megan Mitchell

University of California, Los AngelesORCID 0000-0002-4284-2201Unclaimed 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:differential expression· 2 Assay:DNA methylation· 2 Approach:statistical model· 2 Approach:contrastive learning· 1 Organism:human· 1

Frequent Co-Authors

Lajoyce MboningiD· 2 shared Louis-S. BouchardiD· 2 shared Matteo A. PellegriniiD· 2 shared Nicole Nolan· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

4 top collaborators · 6 mutual co-author links

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2 shared papersBioinformatics

Lajoyce MboningORCID

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2 papers

Recent·Most cited

Conformal Uncertainty Quantification for BayesAge Epigenetic Age Predictions

Megan Mitchell, Lajoyce Mboning, Louis-S. Bouchard, Matteo A. Pellegrini

This paper applies conformal prediction to BayesAge to provide calibrated uncertainty intervals for epigenetic age estimation from DNA methylation data.

bioRxiv · Aug 19, 2026 · PreprintBioinformatics

MicroBayesAge: A Maximum Likelihood Approach to Predict Epigenetic Age Using Microarray Data

Nicole Nolan, Megan Mitchell, Lajoyce Mboning, Louis‐S. Bouchard, Matteo A. Pellegrini

MicroBayesAge improves age prediction using microarray data by dividing data into age-specific cohorts and employing a two-stage process, showing better accuracy for younger patients and males.

GeroScience · May 30, 2025Peer-reviewedBioinformatics