MOTHER-DB:共享非人类卵巢组织学图像的数据库。

IF 3.6 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS IEEE/ACM Transactions on Computational Biology and Bioinformatics Pub Date : 2024-07-12 DOI:10.1109/TCBB.2024.3426999
Suzanne W. Dietrich;Wenli Ma;Yian Ding;Karen H. Watanabe;Mary B. Zelinski;James P. Sluka
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引用次数: 0

摘要

多物种卵巢组织学电子资源库(MOTHER)项目的目标是建立一个多物种非人类卵巢组织学图像库,作为研究人员和教育工作者的资源。共享科学数据的一个重要组成部分是包含描述数据的上下文元数据。MOTHER 扩展了用于记录研究数据的生态元数据语言(EML),利用其数据来源和使用许可,纳入了卵巢组织学图像的元数据。MOTHER 元数据的设计包括供体动物的信息,包括生殖周期状态、切片及其制备。MOTHER 还扩展了 ezEML 工具,称为 ezEML+MOTHER,用于指定元数据。MOTHER 数据库(MOTHERDB)的设计捕获了组织学图像的元数据,为发现相关图像提供了可搜索的资源。MOTHER 还定义了图像及其元数据集合摄取的策划流程,在将元数据纳入 MOTHER 集合之前对其有效性进行验证。网络搜索提供了根据元数据本身的各种特征(如属和种)使用过滤器识别相关图像的能力。
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MOTHER-DB: A Database for Sharing Nonhuman Ovarian Histology Images
The goal of the Multispecies Ovary Tissue Histology Electronic Repository (MOTHER) project is to establish a collection of nonhuman ovary histology images for multiple species as a resource for researchers and educators. An important component of sharing scientific data is the inclusion of the contextual metadata that describes the data. MOTHER extends the Ecological Metadata Language (EML) for documenting research data, leveraging its data provenance and usage license with the inclusion of metadata for ovary histology images. The design of the MOTHER metadata includes information on the donor animal, including reproductive cycle status, the slide and its preparation. MOTHER also extends the ezEML tool, called ezEML+MOTHER, for the specification of the metadata. The design of the MOTHER database (MOTHER-DB) captures the metadata about the histology images, providing a searchable resource for discovering relevant images. MOTHER also defines a curation process for the ingestion of a collection of images and its metadata, verifying the validity of the metadata before its inclusion in the MOTHER collection. A Web search provides the ability to identify relevant images based on various characteristics in the metadata itself, such as genus and species, using filters.
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来源期刊
CiteScore
7.50
自引率
6.70%
发文量
479
审稿时长
3 months
期刊介绍: IEEE/ACM Transactions on Computational Biology and Bioinformatics emphasizes the algorithmic, mathematical, statistical and computational methods that are central in bioinformatics and computational biology; the development and testing of effective computer programs in bioinformatics; the development of biological databases; and important biological results that are obtained from the use of these methods, programs and databases; the emerging field of Systems Biology, where many forms of data are used to create a computer-based model of a complex biological system
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