Role of the biological ontologies in the resources management in the gridтезисы доклада

Работа с тезисами доклада

[1] Role of the biological ontologies in the resources management in the grid / I. G. Strizh, A. Zhuchkov, N. Tverdokhlebov, S. Golitsyn // Тезисы докладов второй международной конференции "Распределенные вычисления и Грид-технологии в науке и образовании". — ОИЯИ Дубна, 2006. — P. 152–152. Effective use of the information is the common problem, particularly in contemporary biology. As it was proposed recently, service-oriented science has the potential to increase individual and collective scientific productivity by making powerful information tools available to all, and thus enabling the widespread automation of data analysis and computation (I.Foster, 2005). Currently, biologists have to work with enormous amount of information and materials, such as nucleotide and amino acid sequences, gene and protein functions, mutants and their phenotypes as well as literature references, produced by the rapid development of high-throughput technologies in this field. These data are commonly spanned across different geographically distributed organizations, therefore efficiently access and effectively analyze remains a nontrivial challenge for many biologists. Making all these data available for scientists through the grid is the prominent challenge. To do this, we got to “gather” diverse data into the subject-oriented grid-content. The powerful tool that already facilitates obtaining, comparing, analyzing and integrating data is ontology. Ontologies are commonly refereed as an explicit specification of a conceptualization where definitions associate concepts, taxonomies, and relationships with human-readable text and formal, machine-readable axioms (Gruber 1993). Ontologies of different kind have been already implemented in Grid. A number of the tasks in Grid that could be effectively solved by ontologies can be listed. One of them is hiding the complexity of Grids from the end-users. For instance, ontologies support scheduling and resource management as well as workflow modeling in emerging Grids. However, contemporary biological ontologies, such as the Gene Ontology (GO) – the one of the best known biological ontologies today – represent a huge storage of information (vocabulary of terms in GO exceeds over 16,000), rather than an effective tool for working with it. It is much more practical to develop task-oriented ontologies as well as grid-services that would provide an ability to link not only data to ontologies, but several ontologies without mixing them also. We have developed the prototype of the subject-oriented biological ontology which let the scientists to join contemporary data and knowledge about reactive oxygen species processing and signaling in plants. Such kind of the subject-oriented ontology provide an ability to transform distributed and diverse data in the particular field into the grid-recourse, thus forming the subject-oriented, biological content in emerging grid.

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