Suppr超能文献

基于 Physiome 模型知识库的模型标注和发现。

Model annotation and discovery with the Physiome Model Repository.

机构信息

Auckland Bioengineering Institute, University of Auckland, Auckland, New Zealand.

Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, Washington, USA.

出版信息

BMC Bioinformatics. 2019 Sep 6;20(1):457. doi: 10.1186/s12859-019-2987-y.

Abstract

BACKGROUND

Mathematics and Phy sics-based simulation models have the potential to help interpret and encapsulate biological phenomena in a computable and reproducible form. Similarly, comprehensive descriptions of such models help to ensure that such models are accessible, discoverable, and reusable. To this end, researchers have developed tools and standards to encode mathematical models of biological systems enabling reproducibility and reuse, tools and guidelines to facilitate semantic description of mathematical models, and repositories in which to archive, share, and discover models. Scientists can leverage these resources to investigate specific questions and hypotheses in a more efficient manner.

RESULTS

We have comprehensively annotated a cohort of models with biological semantics. These annotated models are freely available in the Physiome Model Repository (PMR). To demonstrate the benefits of this approach, we have developed a web-based tool which enables users to discover models relevant to their work, with a particular focus on epithelial transport. Based on a semantic query, this tool will help users discover relevant models, suggesting similar or alternative models that the user may wish to explore or use.

CONCLUSION

The semantic annotation and the web tool we have developed is a new contribution enabling scientists to discover relevant models in the PMR as candidates for reuse in their own scientific endeavours. This approach demonstrates how semantic web technologies and methodologies can contribute to biomedical and clinical research. The source code and links to the web tool are available at https://github.com/dewancse/model-discovery-tool.

摘要

背景

基于数学和物理的模拟模型具有以可计算和可重复的形式帮助解释和封装生物现象的潜力。同样,对这些模型的全面描述有助于确保这些模型是可访问、可发现和可重复使用的。为此,研究人员开发了工具和标准,以对生物系统的数学模型进行编码,从而实现可重复性和可重用性,开发了工具和指南,以促进数学模型的语义描述,并建立了存储库,以存档、共享和发现模型。科学家可以利用这些资源以更有效的方式研究特定的问题和假设。

结果

我们已经全面地为一组具有生物学语义的模型添加了注释。这些经过注释的模型可在 Physiome 模型存储库 (PMR) 中免费获得。为了展示这种方法的好处,我们开发了一个基于网络的工具,使用户能够发现与其工作相关的模型,特别关注上皮细胞转运。基于语义查询,该工具将帮助用户发现相关模型,并建议用户可能希望探索或使用的类似或替代模型。

结论

我们开发的语义注释和网络工具是一个新的贡献,使科学家能够在 PMR 中发现相关模型,作为在自己的科学工作中重复使用的候选模型。这种方法展示了语义 Web 技术和方法如何为生物医学和临床研究做出贡献。该工具的源代码和链接可在 https://github.com/dewancse/model-discovery-tool 上找到。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f07c/6731580/90dd6361af1b/12859_2019_2987_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验