Background:
On a tide of big data, machine learning is coming to its day. Referring to huge amounts
of epigenetic data coming from biological experiments and clinic, machine learning can help in detecting epigenetic
features in genome, finding correlations between phenotypes and modifications in histone or genes, accelerating
the screen of lead compounds targeting epigenetics diseases and many other aspects around the study on
epigenetics, which consequently realizes the hope of precision medicine.
Methods:
In this minireview, we will focus on reviewing the fundamentals and applications of machine learning
methods which are regularly used in epigenetics filed and explain their features. Their advantages and disadvantages
will also be discussed.
Results:
Machine learning algorithms have accelerated studies in precision medicine targeting epigenetics diseases.
Conclusion:
In order to make full use of machine learning algorithms, one should get familiar with the pros and
cons of them, which will benefit from big data by choosing the most suitable method(s).
Harnessing big data for precision medicine: A panel of experts elucidates the data challenges and proposes key strategic decisions points
