Monitoring the evolutionary aspect of the Gene Ontology to enhance predictability and usability.
BACKGROUND
Much effort is currently made to develop the Gene Ontology (GO). Due to the dynamic nature of information it addresses, GO undergoes constant updates whose results are released at regular intervals as separate versions. Although there are a large number of computational tools to aid the development of GO, they are operating on a particular version of GO, making it difficult for GO curators to anticipate the full impact of particular changes along the time axis on a larger scale. We present a method for tapping into such an evolutionary aspect of GO, by making it possible to keep track of important temporal changes to any of the terms and relations of GO and by consequently making it possible to recognize associated trends.


RESULTS
We have developed visualization methods for viewing the changes between two different versions of GO by constructing a colour-coded layered graph. The graph shows both versions of GO with highlights to those GO terms that are added, removed and modified between the two versions. Focusing on a specific GO term or terms of interest over a period, we demonstrate the utility of our system that can be used to make useful hypotheses about the cause of the evolution and to provide new insights into more complex changes.


CONCLUSIONS
GO undergoes fast evolutionary changes. A snapshot of GO, as presented by each version of GO alone, overlooks such evolutionary aspects, and consequently limits the utilities of GO. The method that highlights the differences of consecutive versions or two different versions of an evolving ontology with colour-coding enhances the utility of GO for users as well as for developers. To the best of our knowledge, this is the first proposal to visualize the evolutionary aspect of GO.
Park
Jong C
JC
Computer Science Division, KAIST, 373-1 Guseong-dong, Yuseong-gu, Daejeon, 305-701, South Korea. park@nlp.kaist.ac.kr
Kim
Tak-eun
TE
Park
Jinah
J
D000465:Algorithms; D001185:Artificial Intelligence; D019143:Evolution, Molecular; D005796:Genes / Q000235:genetics*; D009323:Natural Language Processing; D010363:Pattern Recognition, Automated / Q000379:methods*; D011506:Proteins / Q000145:classification* / Q000235:genetics*; D012680:Sensitivity and Specificity; D009626:Terminology as Topic; D018875:Vocabulary, Controlled
D011506:Proteins