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Ontologies for data and knowledge sharing in biology: plant ROS signaling as a case study
Author(s) -
Strizh Irina G.
Publication year - 2006
Publication title -
bioessays
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.175
H-Index - 184
eISSN - 1521-1878
pISSN - 0265-9247
DOI - 10.1002/bies.20368
Subject(s) - ontology , systems biology , data science , computer science , process (computing) , key (lock) , subject (documents) , computational biology , data sharing , biology , world wide web , ecology , epistemology , medicine , philosophy , alternative medicine , pathology , operating system
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. BioEssays 28: 199–210, 2006. © 2006 Wiley periodicals, Inc.