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Resources available for autism research in the big data era: a systematic review
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 o...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5237363/ https://www.ncbi.nlm.nih.gov/pubmed/28097074 http://dx.doi.org/10.7717/peerj.2880 |
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author | Al-jawahiri, Reem Milne, Elizabeth |
author_facet | Al-jawahiri, Reem Milne, Elizabeth |
author_sort | Al-jawahiri, Reem |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5237363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-52373632017-01-17 Resources available for autism research in the big data era: a systematic review Al-jawahiri, Reem Milne, Elizabeth PeerJ Bioinformatics 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. PeerJ Inc. 2017-01-12 /pmc/articles/PMC5237363/ /pubmed/28097074 http://dx.doi.org/10.7717/peerj.2880 Text en ©2017 Al-jawahiri and Milne http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Al-jawahiri, Reem Milne, Elizabeth Resources available for autism research in the big data era: a systematic review |
title | Resources available for autism research in the big data era: a systematic review |
title_full | Resources available for autism research in the big data era: a systematic review |
title_fullStr | Resources available for autism research in the big data era: a systematic review |
title_full_unstemmed | Resources available for autism research in the big data era: a systematic review |
title_short | Resources available for autism research in the big data era: a systematic review |
title_sort | resources available for autism research in the big data era: a systematic review |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5237363/ https://www.ncbi.nlm.nih.gov/pubmed/28097074 http://dx.doi.org/10.7717/peerj.2880 |
work_keys_str_mv | AT aljawahirireem resourcesavailableforautismresearchinthebigdataeraasystematicreview AT milneelizabeth resourcesavailableforautismresearchinthebigdataeraasystematicreview |