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大数据时代可用于自闭症研究的资源:一项系统综述。

Resources available for autism research in the big data era: a systematic review.

作者信息

Al-Jawahiri Reem, Milne Elizabeth

机构信息

Department of Psychology, University of Sheffield , Sheffield , United Kingdom.

出版信息

PeerJ. 2017 Jan 12;5:e2880. doi: 10.7717/peerj.2880. eCollection 2017.

Abstract

Recently, there has been a move encouraged by many stakeholders towards generating big, open data in many areas of research. One area where big, open data is particularly valuable is in research relating to complex heterogeneous disorders such as Autism Spectrum Disorder (ASD). The inconsistencies of findings and the great heterogeneity of ASD necessitate the use of big and open data to tackle important challenges such as understanding and defining the heterogeneity and potential subtypes of ASD. To this end, a number of initiatives have been established that aim to develop big and/or open data resources for autism research. In order to provide a useful data reference for autism researchers, a systematic search for ASD data resources was conducted using the Scopus database, the Google search engine, and the pages on 'recommended repositories' by key journals, and the findings were translated into a comprehensive list focused on ASD data. The aim of this review is to systematically search for all available ASD data resources providing the following data types: phenotypic, neuroimaging, human brain connectivity matrices, human brain statistical maps, biospecimens, and ASD participant recruitment. A total of 33 resources were found containing different types of data from varying numbers of participants. Description of the data available from each data resource, and links to each resource is provided. Moreover, key implications are addressed and underrepresented areas of data are identified.

摘要

最近,在许多利益相关者的推动下,研究的许多领域都在朝着生成大规模开放数据的方向发展。大规模开放数据特别有价值的一个领域是与自闭症谱系障碍(ASD)等复杂异质性疾病相关的研究。ASD研究结果的不一致性以及其巨大的异质性使得有必要使用大规模开放数据来应对一些重要挑战,比如理解和定义ASD的异质性及潜在亚型。为此,已经开展了一些旨在为自闭症研究开发大规模和/或开放数据资源的倡议。为了为自闭症研究人员提供有用的数据参考,我们使用Scopus数据库、谷歌搜索引擎以及主要期刊“推荐存储库”页面,对ASD数据资源进行了系统搜索,并将结果转化为一份专注于ASD数据的综合列表。本综述的目的是系统搜索所有可用的ASD数据资源,这些资源需提供以下数据类型:表型数据、神经影像数据、人脑连接矩阵、人脑统计图、生物样本以及ASD参与者招募信息。共发现33个资源,包含来自不同数量参与者的不同类型数据。文中提供了每个数据资源的可用数据描述以及各资源的链接。此外,还阐述了关键影响并确定了数据中代表性不足的领域。

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