Improving the interoperability of biomedical ontologies with compound alignments.
Improving the interoperability of biomedical ontologies with compound alignments.
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DOI：
10.1186/s13326-017-0171-8
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发表时间：
2018-01-09
影响因子：
1.9
通讯作者：
Pesquita C
中科院分区：
文献类型：
--
作者：
Oliveira D;Pesquita C
本体论通常用于注释和帮助处理生命科学数据。尽管它们最初的目标是促进不同数据源之间的集成和互操作性，但当这些数据源使用不同的本体进行注释时，弥合这一差距可能是具有挑战性的。在过去的十年中，本体匹配系统一直在发展，现在能够为生命科学本体产生高质量的映射，通常限于两个本体之间的等价性。然而，生命科学研究正变得越来越跨学科和一体化，这促使人们需要开发能够处理多个本体及其概念之间更复杂关系的匹配策略。我们已经开发了本体匹配算法，该算法能够以三元映射的形式找到多个生物医学本体之间的复合映射，例如，发现“主动脉瓣狭窄”(HP：0001650)等同于“主动脉瓣”(FMA：7236)和“狭窄”(PATO：0001847)之间的交集。该算法利用基于本体对之间部分映射的搜索空间过滤，能够处理增加的计算需求。对算法的评估表明，它们能够产生有意义的结果，新映射的精度在60%-92%的范围内。这些算法还被应用于OBO逻辑定义的潜在扩展和几个与植物相关的本体的匹配。这项工作是朝着寻找多个本体之间更复杂的关系迈出的第一步。评估结果表明，所产生的结果是显著的，算法能够满足特定的集成需求。
Ontologies are commonly used to annotate and help process life sciences data. Although their original goal is to facilitate integration and interoperability among heterogeneous data sources, when these sources are annotated with distinct ontologies, bridging this gap can be challenging. In the last decade, ontology matching systems have been evolving and are now capable of producing high-quality mappings for life sciences ontologies, usually limited to the equivalence between two ontologies. However, life sciences research is becoming increasingly transdisciplinary and integrative, fostering the need to develop matching strategies that are able to handle multiple ontologies and more complex relations between their concepts. We have developed ontology matching algorithms that are able to find compound mappings between multiple biomedical ontologies, in the form of ternary mappings, finding for instance that “aortic valve stenosis”(HP:0001650) is equivalent to the intersection between “aortic valve”(FMA:7236) and “constricted” (PATO:0001847). The algorithms take advantage of search space filtering based on partial mappings between ontology pairs, to be able to handle the increased computational demands. The evaluation of the algorithms has shown that they are able to produce meaningful results, with precision in the range of 60-92% for new mappings. The algorithms were also applied to the potential extension of logical definitions of the OBO and the matching of several plant-related ontologies. This work is a first step towards finding more complex relations between multiple ontologies. The evaluation shows that the results produced are significant and that the algorithms could satisfy specific integration needs.
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影响因子：
4.9
作者：
Cooper L;Walls RL;Elser J;Gandolfo MA;Stevenson DW;Smith B;Preece J;Athreya B;Mungall CJ;Rensing S;Hiss M;Lang D;Reski R;Berardini TZ;Li D;Huala E;Schaeffer M;Menda N;Arnaud E;Shrestha R;Yamazaki Y;Jaiswal P
通讯作者：
Jaiswal P
影响因子：
14.9
作者：
Köhler S;Doelken SC;Mungall CJ;Bauer S;Firth HV;Bailleul-Forestier I;Black GC;Brown DL;Brudno M;Campbell J;FitzPatrick DR;Eppig JT;Jackson AP;Freson K;Girdea M;Helbig I;Hurst JA;Jähn J;Jackson LG;Kelly AM;Ledbetter DH;Mansour S;Martin CL;Moss C;Mumford A;Ouwehand WH;Park SM;Riggs ER;Scott RH;Sisodiya S;Van Vooren S;Wapner RJ;Wilkie AO;Wright CF;Vulto-van Silfhout AT;de Leeuw N;de Vries BB;Washingthon NL;Smith CL;Westerfield M;Schofield P;Ruef BJ;Gkoutos GV;Haendel M;Smedley D;Lewis SE;Robinson PN
通讯作者：
Robinson PN
影响因子：
12.3
作者：
Mungall CJ;Gkoutos GV;Smith CL;Haendel MA;Lewis SE;Ashburner M
通讯作者：
Ashburner M
使用证据内容在文本中找到基因组本体术语。
影响因子：
3
作者：
Couto, FM;Silva, MJ;Coutinho, PM
通讯作者：
Coutinho, PM
影响因子：
4.2
作者：
Doan, A;Madhavan, J;Halevy, A
通讯作者：
Halevy, A