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Constructing a database for the relations between CNV and human genetic diseases via systematic text mining
BACKGROUND: The detection and interpretation of CNVs are of clinical importance in genetic testing. Several databases and web services are already being used by clinical geneticists to interpret the medical relevance of identified CNVs in patients. However, geneticists or physicians would like to ob...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311945/ https://www.ncbi.nlm.nih.gov/pubmed/30598077 http://dx.doi.org/10.1186/s12859-018-2526-2 |
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author | Yang, Xi Song, Zhuo Wu, Chengkun Wang, Wei Li, Gen Zhang, Wei Wu, Lingqian Lu, Kai |
author_facet | Yang, Xi Song, Zhuo Wu, Chengkun Wang, Wei Li, Gen Zhang, Wei Wu, Lingqian Lu, Kai |
author_sort | Yang, Xi |
collection | PubMed |
description | BACKGROUND: The detection and interpretation of CNVs are of clinical importance in genetic testing. Several databases and web services are already being used by clinical geneticists to interpret the medical relevance of identified CNVs in patients. However, geneticists or physicians would like to obtain the original literature context for more detailed information, especially for rare CNVs that were not included in databases. RESULTS: The resulting CNVdigest database includes 440,485 sentences for CNV-disease relationship. A total number of 1582 CNVs and 2425 diseases are involved. Sentences describing CNV-disease correlations are indexed in CNVdigest, with CNV mentions and disease mentions annotated. CONCLUSIONS: In this paper, we use a systematic text mining method to construct a database for the relationship between CNVs and diseases. Based on that, we also developed a concise front-end to facilitate the analysis of CNV/disease association, providing a user-friendly web interface for convenient queries. The resulting system is publically available at http://cnv.gtxlab.com/. |
format | Online Article Text |
id | pubmed-6311945 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63119452019-01-07 Constructing a database for the relations between CNV and human genetic diseases via systematic text mining Yang, Xi Song, Zhuo Wu, Chengkun Wang, Wei Li, Gen Zhang, Wei Wu, Lingqian Lu, Kai BMC Bioinformatics Research BACKGROUND: The detection and interpretation of CNVs are of clinical importance in genetic testing. Several databases and web services are already being used by clinical geneticists to interpret the medical relevance of identified CNVs in patients. However, geneticists or physicians would like to obtain the original literature context for more detailed information, especially for rare CNVs that were not included in databases. RESULTS: The resulting CNVdigest database includes 440,485 sentences for CNV-disease relationship. A total number of 1582 CNVs and 2425 diseases are involved. Sentences describing CNV-disease correlations are indexed in CNVdigest, with CNV mentions and disease mentions annotated. CONCLUSIONS: In this paper, we use a systematic text mining method to construct a database for the relationship between CNVs and diseases. Based on that, we also developed a concise front-end to facilitate the analysis of CNV/disease association, providing a user-friendly web interface for convenient queries. The resulting system is publically available at http://cnv.gtxlab.com/. BioMed Central 2018-12-31 /pmc/articles/PMC6311945/ /pubmed/30598077 http://dx.doi.org/10.1186/s12859-018-2526-2 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Yang, Xi Song, Zhuo Wu, Chengkun Wang, Wei Li, Gen Zhang, Wei Wu, Lingqian Lu, Kai Constructing a database for the relations between CNV and human genetic diseases via systematic text mining |
title | Constructing a database for the relations between CNV and human genetic diseases via systematic text mining |
title_full | Constructing a database for the relations between CNV and human genetic diseases via systematic text mining |
title_fullStr | Constructing a database for the relations between CNV and human genetic diseases via systematic text mining |
title_full_unstemmed | Constructing a database for the relations between CNV and human genetic diseases via systematic text mining |
title_short | Constructing a database for the relations between CNV and human genetic diseases via systematic text mining |
title_sort | constructing a database for the relations between cnv and human genetic diseases via systematic text mining |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311945/ https://www.ncbi.nlm.nih.gov/pubmed/30598077 http://dx.doi.org/10.1186/s12859-018-2526-2 |
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