ComputationalAgingLab/ComputAge

A library for full-stack aging clocks design and benchmarking.

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Experimental

This tool helps researchers and bioinformaticians working on aging research to develop and rigorously test new 'aging clocks.' It takes DNA methylation data (specifically CpG site levels) from biological samples and uses it to predict an individual's chronological and biological age. The output helps evaluate how well new aging clock models perform against established benchmarks, especially in predicting age acceleration in specific health conditions.

No commits in the last 6 months.

Use this if you are a researcher developing or evaluating machine learning models designed to predict age from DNA methylation data and need a standardized way to benchmark their performance against known aging-accelerating conditions.

Not ideal if you are a clinician looking for a diagnostic tool for biological age or if your research doesn't involve epigenetic data.

aging-research epigenetics bioinformatics biomarker-discovery biological-age-prediction
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 6 / 25

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Stars

36

Forks

2

Language

Jupyter Notebook

License

CC-BY-SA-4.0

Last pushed

Jan 29, 2025

Commits (30d)

0

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