Lajoyce Mboning

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

MKMC enables reference-free transcriptomic analysis using k-mer representations, detecting isoform-specific events and matching alignment-based methods in differential expression and age prediction.

The paper creates a multi-tissue transcriptomic aging atlas in killifish, identifies age-altered pathways, and develops tissue-specific transcriptomic clocks with sex-specific biomarkers for aging prediction.

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.

BayesAge 2.0 predicts transcriptomic age from RNA-seq data using a maximum likelihood algorithm with Poisson distribution and LOWESS smoothing, improving accuracy and efficiency over traditional models.

BayesAge predicts epigenetic age using maximum likelihood estimation and binomial models for bulk bisulfite sequencing data, outperforming scAge in accuracy and interpretability.