Title:Artificial Intelligence for Epigenetics: Towards Personalized Medicine
Volume: 28
Issue: 32
关键词:
人工智能、个性化医疗、机器学习、数据挖掘、表观基因组学、多组学。
摘要:
Epigenetics is a field of biological sciences focused on the study of reversible,
heritable changes in gene function, not due to modifications of the genomic sequence. These
changes are the result of a complex cross-talk between several molecular mechanisms
that is in turn orchestrated by genetic and environmental factors. The epigenetic
profile captures the unique regulatory landscape and the exposure to environmental stimuli
of an individual. It thus constitutes a valuable reservoir of information for personalized
medicine, which is aimed at customizing health-care interventions based on the
unique characteristics of each individual.
Nowadays, the complex milieu of epigenomic marks can be studied at the genome-wide
level thanks to massive, high-throughput technologies. This new experimental approach
is opening up new and interesting knowledge perspectives. However, the analysis of these
complex omic data requires to face important analytic issues.
Artificial Intelligence, and in particular Machine Learning, are emerging as powerful resources
to decipher epigenomic data. In this review, we will first describe the most used
ML approaches in epigenomics. We then will recapitulate some of the recent applications
of ML to epigenomic analysis. Finally, we will provide some examples of how the
ML approach to epigenetic data can be useful for personalized medicine.
