干细胞研究统一智能整合的信息学方法。

IF 1.7 Q4 CELL BIOLOGY Stem Cells and Cloning-Advances and Applications Pub Date : 2020-01-28 eCollection Date: 2020-01-01 DOI:10.2147/SCCAA.S237361
Joseph Finkelstein, Irena Parvanova, Frederick Zhang
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引用次数: 0

摘要

随着生物医学数据整合与分析在干细胞研究领域发挥越来越大的作用,开发研究人员之间标准化、汇总和共享数据的方法变得非常重要。为此,近年来开发了许多数据库,试图同时将不同干细胞项目和实验的数据进行系统化存储。然而,这些数据库在实施和结构上差异很大。本范围综述旨在描述现有干细胞数据库的主要特征,以确定有助于未来干细胞数据库实施的规范。我们对同行评审文献和在线资源进行了范围界定审查,以确定和审查现有干细胞数据库。为了确定相关数据库,我们使用相关的MeSH术语进行了PubMed搜索,然后对可能没有相关期刊文章的数据库进行了网络搜索。我们总共确定了 16 个数据库纳入本综述。这些数据库中报告的数据元素代表了从基本社会人口变量到各种细胞特征、细胞表面标志物表达和临床试验结果等广泛的参数。我们确定了三大功能特征集,这些特征集可为未来干细胞研究提供有用信息,并促进生物信息学工作流程。这些功能包括:通用数据元素、数据可视化和分析工具,以及用于数据整合的生物医学本体。干细胞生物信息学是一个快速发展的领域,它产生了越来越多的异构数据集。开发用于智能干细胞数据聚合、共享和协作过程的应用程序,可大大促进干细胞研究的进一步发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Informatics Approaches for Harmonized Intelligent Integration of Stem Cell Research.

As biomedical data integration and analytics play an increasing role in the field of stem cell research, it becomes important to develop ways to standardize, aggregate, and share data among researchers. For this reason, many databases have been developed in recent years in an attempt to systematically warehouse data from different stem cell projects and experiments at the same time. However, these databases vary widely in their implementation and structure. The aim of this scoping review is to characterize the main features of available stem cell databases in order to identify specifications useful for implementation in future stem cell databases. We conducted a scoping review of peer-reviewed literature and online resources to identify and review available stem cell databases. To identify the relevant databases, we performed a PubMed search using relevant MeSH terms followed by a web search for databases which may not have an associated journal article. In total, we identified 16 databases to include in this review. The data elements reported in these databases represented a broad spectrum of parameters from basic socio-demographic variables to various cells characteristics, cell surface markers expression, and clinical trial results. Three broad sets of functional features that provide utility for future stem cell research and facilitate bioinformatics workflows were identified. These features consisted of the following: common data elements, data visualization and analysis tools, and biomedical ontologies for data integration. Stem cell bioinformatics is a quickly evolving field that generates a growing number of heterogeneous data sets. Further progress in the stem cell research may be greatly facilitated by development of applications for intelligent stem cell data aggregation, sharing and collaboration process.

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来源期刊
CiteScore
6.50
自引率
0.00%
发文量
10
审稿时长
16 weeks
期刊最新文献
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