Ontologies for data and knowledge sharing in biology: plant ROS signaling as a case study

Abstract

Modern technologies have rapidly transformed biology into a data-intensive discipline. In addition to the enormous amounts of existing experimental data in the literature, every new study can produce a large amount of new data, resulting in novel ideas and more publications. In order to understand a biological process as completely as possible, scientists should be able to combine and analyze all such information. Not only molecular biology and bioinformatics, but all the other domains of biology including plant biology, require tools and technologies that enable experts to capture knowledge within distributed and heterogeneous sources of information. Ontologies have proven to be one of the most-useful means of constructing and formalizing expert knowledge. The key feature of an ontology is that it represents a computer-interpretable model of a particular subject area. This article outlines the importance of ontologies for systems biology, data integration and information analyses, as illustrated through the example of reactive oxygen species (ROS) signaling networks in plants.

A semantic web approach applied to integrative bioinformatics experimentation: a biological use case with genomics data

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A multilevel data integration resource for breast cancer study

“…Other than representing an important instrument for generating new hypotheses and producing novel knowledge [30], the ontology layer which underlies the database structure improves the user capability of browsing data, due to the available standardised terms and the connection map provided by the ontology tree. GO terms and KEGG pathways are browsable through a section where the GO directed acyclic graph and the KEGG pathways hierarchy tree are available.…”

Sharing e-Health Information through Ontological Layering

“…The ontology from [34] is used for organizing and sharing large sets of data, produced by Reactive Oxygen Species (ROS) signaling networks in plants. The ontological model formalizes the data sets according to a shared set of agreed concepts.…”