Computational Epigenetics: the new scientific paradigm

Abstract

Epigenetics has recently emerged as a critical field for studying how non-gene factors can influence the traits and functions of an organism. At the core of this new wave of research is the use of computational tools that play critical roles not only in directing the selection of key experiments, but also in formulating new testable hypotheses through detailed analysis of complex genomic information that is not achievable using traditional approaches alone. Epigenomics, which combines traditional genomics with computer science, mathematics, chemistry, biochemistry and proteomics for the large-scale analysis of heritable changes in phenotype, gene function or gene expression that are not dependent on gene sequence, offers new opportunities to further our understanding of transcriptional regulation, nuclear organization, development and disease. This article examines existing computational strategies for the study of epigenetic factors. The most important databases and bioinformatic tools in this rapidly growing field have been reviewed.

Epigenetic mechanisms in sexual differentiation of the brain and behaviour

“…Second, it seems inevitable that computational and statistical methods will play an ever-increasing role in those studies with an epigenetic component. The new field of computational epigenetics [78] holds some promise for dealing with the enormous combinatorial complexity of epigenetic mechanisms; the hope is that these tools may point us to new, testable hypotheses and allow for progress not possible using traditional approaches alone.…”

Basic concepts of epigenetics

“…On the other hand, the environmental and biological controls that mediate these events are extraordinary in number, compounded by instances of similar methylation events that have opposite effects when occurring at different histone amino acids (e.g., H3K36me3 and H3K9me3) and by variation in the interpretation of studies performed in diverse organisms such as flies, plants, worms, yeast, ciliated protozoans, tumor cells and mammals. 31 …”

Recent advances in computational epigenetics

“…69 Specific efforts for epigenetic measures have focused on DNA methylation content and patterns, as well as chromatin-associated proteins and methylated genes in various cancer types and other diseases. The value of the data types has been discussed in articles, including the one by Bock and Lengauer 70 which describes inferences on epigenetic states from DNA sequences and the one by Lim et al 71 which also reviews contemporary databases and tools, and more recently still through shared internet resources, such as Epigenie 72 which incorporates information on current large-scale projects, databases by data type and statistical data analysis and visualization tools.…”