生物测定本体的扩展,包括药代动力学/药效学术语,以丰富科学工作流程。

IF 1.6 3区 工程技术 Q3 MATHEMATICAL & COMPUTATIONAL BIOLOGY Journal of Biomedical Semantics Pub Date : 2023-08-11 DOI:10.1186/s13326-023-00288-6
Steve Penn, Jane Lomax, Anneli Karlsson, Vincent Antonucci, Carl-Dieter Zachmann, Samantha Kanza, Stephan Schurer, John Turner
{"title":"生物测定本体的扩展,包括药代动力学/药效学术语,以丰富科学工作流程。","authors":"Steve Penn, Jane Lomax, Anneli Karlsson, Vincent Antonucci, Carl-Dieter Zachmann, Samantha Kanza, Stephan Schurer, John Turner","doi":"10.1186/s13326-023-00288-6","DOIUrl":null,"url":null,"abstract":"<p><p>With the capacity to produce and record data electronically, Scientific research and the data associated with it have grown at an unprecedented rate. However, despite a decent amount of data now existing in an electronic form, it is still common for scientific research to be recorded in an unstructured text format with inconsistent context (vocabularies) which vastly reduces the potential for direct intelligent analysis. Research has demonstrated that the use of semantic technologies such as ontologies to structure and enrich scientific data can greatly improve this potential. However, whilst there are many ontologies that can be used for this purpose, there is still a vast quantity of scientific terminology that does not have adequate semantic representation. A key area for expansion identified by the authors was the pharmacokinetic/pharmacodynamic (PK/PD) domain due to its high usage across many areas of Pharma. As such we have produced a set of these terms and other bioassay related terms to be incorporated into the BioAssay Ontology (BAO), which was identified as the most relevant ontology for this work. A number of use cases developed by experts in the field were used to demonstrate how these new ontology terms can be used, and to set the scene for the continuation of this work with a look to expanding this work out into further relevant domains. The work done in this paper was part of Phase 1 of the SEED project (Semantically Enriching electronic laboratory notebook (eLN) Data).</p>","PeriodicalId":15055,"journal":{"name":"Journal of Biomedical Semantics","volume":"14 1","pages":"10"},"PeriodicalIF":1.6000,"publicationDate":"2023-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10416407/pdf/","citationCount":"0","resultStr":"{\"title\":\"An extension of the BioAssay Ontology to include pharmacokinetic/pharmacodynamic terminology for the enrichment of scientific workflows.\",\"authors\":\"Steve Penn, Jane Lomax, Anneli Karlsson, Vincent Antonucci, Carl-Dieter Zachmann, Samantha Kanza, Stephan Schurer, John Turner\",\"doi\":\"10.1186/s13326-023-00288-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>With the capacity to produce and record data electronically, Scientific research and the data associated with it have grown at an unprecedented rate. However, despite a decent amount of data now existing in an electronic form, it is still common for scientific research to be recorded in an unstructured text format with inconsistent context (vocabularies) which vastly reduces the potential for direct intelligent analysis. Research has demonstrated that the use of semantic technologies such as ontologies to structure and enrich scientific data can greatly improve this potential. However, whilst there are many ontologies that can be used for this purpose, there is still a vast quantity of scientific terminology that does not have adequate semantic representation. A key area for expansion identified by the authors was the pharmacokinetic/pharmacodynamic (PK/PD) domain due to its high usage across many areas of Pharma. As such we have produced a set of these terms and other bioassay related terms to be incorporated into the BioAssay Ontology (BAO), which was identified as the most relevant ontology for this work. A number of use cases developed by experts in the field were used to demonstrate how these new ontology terms can be used, and to set the scene for the continuation of this work with a look to expanding this work out into further relevant domains. The work done in this paper was part of Phase 1 of the SEED project (Semantically Enriching electronic laboratory notebook (eLN) Data).</p>\",\"PeriodicalId\":15055,\"journal\":{\"name\":\"Journal of Biomedical Semantics\",\"volume\":\"14 1\",\"pages\":\"10\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2023-08-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10416407/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Biomedical Semantics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1186/s13326-023-00288-6\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Biomedical Semantics","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1186/s13326-023-00288-6","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
引用次数: 0

摘要

由于能够以电子方式产生和记录数据,科学研究和与之相关的数据以前所未有的速度增长。然而,尽管现在有相当数量的数据以电子形式存在,科学研究仍然普遍以不一致的上下文(词汇表)的非结构化文本格式记录,这大大降低了直接智能分析的潜力。研究表明,使用语义技术(如本体)来构建和丰富科学数据可以极大地提高这种潜力。然而,虽然有许多本体可以用于此目的,但仍然有大量的科学术语没有足够的语义表示。作者确定的一个关键扩展领域是药代动力学/药效学(PK/PD)领域,因为它在制药的许多领域都有很高的使用。因此,我们已经制作了一套这些术语和其他生物测定相关术语,并将其纳入生物测定本体(BAO),该本体被确定为与本工作最相关的本体。由该领域的专家开发的许多用例被用来演示如何使用这些新的本体术语,并为这项工作的继续设置场景,以期将这项工作扩展到进一步的相关领域。本文所做的工作是SEED项目(语义丰富电子实验室笔记本(eLN)数据)第一阶段的一部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
An extension of the BioAssay Ontology to include pharmacokinetic/pharmacodynamic terminology for the enrichment of scientific workflows.

With the capacity to produce and record data electronically, Scientific research and the data associated with it have grown at an unprecedented rate. However, despite a decent amount of data now existing in an electronic form, it is still common for scientific research to be recorded in an unstructured text format with inconsistent context (vocabularies) which vastly reduces the potential for direct intelligent analysis. Research has demonstrated that the use of semantic technologies such as ontologies to structure and enrich scientific data can greatly improve this potential. However, whilst there are many ontologies that can be used for this purpose, there is still a vast quantity of scientific terminology that does not have adequate semantic representation. A key area for expansion identified by the authors was the pharmacokinetic/pharmacodynamic (PK/PD) domain due to its high usage across many areas of Pharma. As such we have produced a set of these terms and other bioassay related terms to be incorporated into the BioAssay Ontology (BAO), which was identified as the most relevant ontology for this work. A number of use cases developed by experts in the field were used to demonstrate how these new ontology terms can be used, and to set the scene for the continuation of this work with a look to expanding this work out into further relevant domains. The work done in this paper was part of Phase 1 of the SEED project (Semantically Enriching electronic laboratory notebook (eLN) Data).

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Journal of Biomedical Semantics
Journal of Biomedical Semantics MATHEMATICAL & COMPUTATIONAL BIOLOGY-
CiteScore
4.20
自引率
5.30%
发文量
28
审稿时长
30 weeks
期刊介绍: Journal of Biomedical Semantics addresses issues of semantic enrichment and semantic processing in the biomedical domain. The scope of the journal covers two main areas: Infrastructure for biomedical semantics: focusing on semantic resources and repositories, meta-data management and resource description, knowledge representation and semantic frameworks, the Biomedical Semantic Web, and semantic interoperability. Semantic mining, annotation, and analysis: focusing on approaches and applications of semantic resources; and tools for investigation, reasoning, prediction, and discoveries in biomedicine.
期刊最新文献
Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI). MeSH2Matrix: combining MeSH keywords and machine learning for biomedical relation classification based on PubMed. Annotation of epilepsy clinic letters for natural language processing An extensible and unifying approach to retrospective clinical data modeling: the BrainTeaser Ontology. Concretizing plan specifications as realizables within the OBO foundry.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1