Biological Ontologies and Semantic Biology

As the amount of biological information and its diversity accumulates massively there is a critical need to facilitate the integration of this data to allow new and unexpected conclusions to be drawn from it. The Semantic Web is a new wave of web- based technologies that allows the linking of data b...

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Հիմնական հեղինակ: John Hancock
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Հրապարակվել է: Frontiers Media SA 2021
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Առցանց հասանելիություն:17785
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author John Hancock
author_browse John Hancock
author_facet John Hancock
author_sort John Hancock
collection Directory of Open Access Books
description As the amount of biological information and its diversity accumulates massively there is a critical need to facilitate the integration of this data to allow new and unexpected conclusions to be drawn from it. The Semantic Web is a new wave of web- based technologies that allows the linking of data between diverse data sets via standardised data formats (“big data”). Semantic Biology is the application of semantic web technology in the biological domain (including medical and health informatics). The Special Topic encompasses papers in this very broad area, including not only ontologies (development and applications), but also text mining, data integration and data analysis making use of the technologies of the Semantic Web. Ontologies are a critical requirement for such integration as they allow conclusions drawn about biological experiments, or descriptions of biological entities, to be understandable and integratable despite being contained in different databases and analysed by different software systems. Ontologies are the standard structures used in biology, and more broadly in computer science, to hold standardized terminologies for particular domains of knowledge. Ontologies consist of sets of standard terms, which are defined and may have synonyms for ease of searching and to accommodate different usages by different communities. These terms are linked by standard relationships, such as “is_a” (an eye “is_a” sense organ) or “part_of” (an eye is “part_of” a head). By linking terms in this way, more detailed, or granular, terms can be linked to broader terms, allowing computation to be carried out that takes these relationships into account.
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spelling doab-20.500.12854ir-422302024-04-05T12:35:09Z Biological Ontologies and Semantic Biology John Hancock QH426-470 TP248.13-248.65 TA1-2040 QK1-989 Q1-390 Semantic Web data representation data analysis ontologies semantic biology thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical) As the amount of biological information and its diversity accumulates massively there is a critical need to facilitate the integration of this data to allow new and unexpected conclusions to be drawn from it. The Semantic Web is a new wave of web- based technologies that allows the linking of data between diverse data sets via standardised data formats (“big data”). Semantic Biology is the application of semantic web technology in the biological domain (including medical and health informatics). The Special Topic encompasses papers in this very broad area, including not only ontologies (development and applications), but also text mining, data integration and data analysis making use of the technologies of the Semantic Web. Ontologies are a critical requirement for such integration as they allow conclusions drawn about biological experiments, or descriptions of biological entities, to be understandable and integratable despite being contained in different databases and analysed by different software systems. Ontologies are the standard structures used in biology, and more broadly in computer science, to hold standardized terminologies for particular domains of knowledge. Ontologies consist of sets of standard terms, which are defined and may have synonyms for ease of searching and to accommodate different usages by different communities. These terms are linked by standard relationships, such as “is_a” (an eye “is_a” sense organ) or “part_of” (an eye is “part_of” a head). By linking terms in this way, more detailed, or granular, terms can be linked to broader terms, allowing computation to be carried out that takes these relationships into account. 2021-02-11T09:09:11Z 2021-02-11T09:09:11Z 2015-12-03 13:02:24 2014 book 17785 16648714 9782889192779 https://directory.doabooks.org/handle/20.500.12854/42230 eng Frontiers Research Topics image/jpeg Attribution 4.0 International http://www.frontiersin.org/books/Biological_Ontologies_and_Semantic_Biology/326 http://journal.frontiersin.org/researchtopic/380/biological-ontologies-and-semantic-biology Frontiers Media SA 10.3389/978-2-88919-277-9 10.3389/978-2-88919-277-9 bf5ce210-e72e-4860-ba9b-c305640ff3ae 9782889192779 106 open access
spellingShingle QH426-470
TP248.13-248.65
TA1-2040
QK1-989
Q1-390
Semantic Web
data representation
data analysis
ontologies
semantic biology
thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical)
John Hancock
Biological Ontologies and Semantic Biology
title Biological Ontologies and Semantic Biology
title_full Biological Ontologies and Semantic Biology
title_fullStr Biological Ontologies and Semantic Biology
title_full_unstemmed Biological Ontologies and Semantic Biology
title_short Biological Ontologies and Semantic Biology
title_sort biological ontologies and semantic biology
topic QH426-470
TP248.13-248.65
TA1-2040
QK1-989
Q1-390
Semantic Web
data representation
data analysis
ontologies
semantic biology
thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical)
topic_facet QH426-470
TP248.13-248.65
TA1-2040
QK1-989
Q1-390
Semantic Web
data representation
data analysis
ontologies
semantic biology
thema EDItEUR::P Mathematics and Science::PS Biology, life sciences::PSA Life sciences: general issues::PSAK Genetics (non-medical)
url 17785
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