The Epigenome Ontology (EGO) is a biomedical ontology for integrative epigenome knowledge representation and data analysis.
The majority of eukaryotic genomes such as those of the human and mouse is noncoding. In eukaryote genomes, basic biological functions such as gene expression are affected by many regulatory elements located outside the coding region of the genome. Unlike the genome, which is largely static across tissues and cells within an individual, the epigenome is cell type specific and can be dynamically altered by environmental conditions. Better epigenomic understanding is critical for uncovering biological mechanisms and disease etiology.
Our understanding of the epigenome has dramatically improved in the past decade thanks to the efforts of several large international consortia, e.g., the Encyclopedia of DNA Elements (ENCODE; https://www.encodeproject.org/). As more and more cells and cell lines are being profiled, combined with more factors being studied, it becomes difficult to track all the experiments and resulting knowledge. In particular, many of the experiments are related due to the fact that either the cell types, or the experimental factors are related or both. Thus it is inadvisable to treat these data as independent.
For better interpretation, the subtle and complicated relationships among these experiments should be more fully considered to achieve a better interpretation. Specifically, a well-defined ontology system that handles complex relationships within a rigorous framework and offers annotation at various levels of granularity would be particularly effective. Towards such goals, we developed the Epigenome Ontology (EGO).
Citation:
He Y, Zheng J, Qin Z. EGO: a biomedical ontology for integrative epigenome representation and analysis. International Conference on Biomedical Ontologies (ICBO-2016), August 1-4, 2016, Oregon State University, Corvallis, OR, USA. 2-page proceeding paper. URL: http://ceur-ws.org/Vol-1747/IP04_ICBO2016.pdf