Publications by authors named "Lajoyce Mboning"
Aging is a complex biological process influenced by various factors, including genetic and environmental influences. In this study, we present BayesAge 2.0, an upgraded version of our maximum likelihood algorithm designed for predicting transcriptomic age (tAge) from RNA-seq data.
View Article and Find Full Text PDFAging is a complex biological process influenced by various factors, including genetic and environmental influences. In this study, we present BayesAge 2.0, an improved version of our maximum likelihood algorithm designed for predicting transcriptomic age (tAge) from RNA-seq data.
View Article and Find Full Text PDFArticle Synopsis
- Chronological age is how many years someone has lived, while biological age shows how well their body is functioning, and this can vary even among people of the same age.
- Scientists are trying to create ways to measure biological age in dogs by studying different dog breeds since they have different lifespans.
- Research on dogs using special tests called methylation shows that it's challenging to find clear biological age markers, and we need to consider the differences among dog breeds to make better predictions.
DNA methylation, specifically the formation of 5-methylcytosine at the C5 position of cytosine, undergoes reproducible changes as organisms age, establishing it as a significant biomarker in aging studies. Epigenetic clocks, which integrate methylation patterns to predict age, often employ linear models based on penalized regression, yet they encounter challenges in handling missing data, count-based bisulfite sequence data, and interpretation. To address these limitations, we introduce BayesAge, an extension of the scAge methodology originally designed for single-cell DNA methylation analysis.
View Article and Find Full Text PDF