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LipiDisease: associate lipids to diseases using literature mining
SUMMARY: Lipids exhibit an essential role in cellular assembly and signaling. Dysregulation of these functions has been linked with many complications including obesity, diabetes, metabolic disorders, cancer and more. Investigating lipid profiles in such conditions can provide insights into cellular...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8686672/ https://www.ncbi.nlm.nih.gov/pubmed/34358314 http://dx.doi.org/10.1093/bioinformatics/btab559 |
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author | More, Piyush Bindila, Laura Wild, Philipp Andrade-Navarro, Miguel Fontaine, Jean-Fred |
author_facet | More, Piyush Bindila, Laura Wild, Philipp Andrade-Navarro, Miguel Fontaine, Jean-Fred |
author_sort | More, Piyush |
collection | PubMed |
description | SUMMARY: Lipids exhibit an essential role in cellular assembly and signaling. Dysregulation of these functions has been linked with many complications including obesity, diabetes, metabolic disorders, cancer and more. Investigating lipid profiles in such conditions can provide insights into cellular functions and possible interventions. Hence the field of lipidomics is expanding in recent years. Even though the role of individual lipids in diseases has been investigated, there is no resource to perform disease enrichment analysis considering the cumulative association of a lipid set. To address this, we have implemented the LipiDisease web server. The tool analyzes millions of records from the PubMed biomedical literature database discussing lipids and diseases, predicts their association and ranks them according to false discovery rates generated by random simulations. The tool takes into account 4270 diseases and 4798 lipids. Since the tool extracts the information from PubMed records, the number of diseases and lipids will be expanded over time as the biomedical literature grows. AVAILABILITY AND IMPLEMENTATION: The LipiDisease webserver can be freely accessed at http://cbdm-01.zdv.uni-mainz.de:3838/piyusmor/LipiDisease/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8686672 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-86866722021-12-21 LipiDisease: associate lipids to diseases using literature mining More, Piyush Bindila, Laura Wild, Philipp Andrade-Navarro, Miguel Fontaine, Jean-Fred Bioinformatics Applications Notes SUMMARY: Lipids exhibit an essential role in cellular assembly and signaling. Dysregulation of these functions has been linked with many complications including obesity, diabetes, metabolic disorders, cancer and more. Investigating lipid profiles in such conditions can provide insights into cellular functions and possible interventions. Hence the field of lipidomics is expanding in recent years. Even though the role of individual lipids in diseases has been investigated, there is no resource to perform disease enrichment analysis considering the cumulative association of a lipid set. To address this, we have implemented the LipiDisease web server. The tool analyzes millions of records from the PubMed biomedical literature database discussing lipids and diseases, predicts their association and ranks them according to false discovery rates generated by random simulations. The tool takes into account 4270 diseases and 4798 lipids. Since the tool extracts the information from PubMed records, the number of diseases and lipids will be expanded over time as the biomedical literature grows. AVAILABILITY AND IMPLEMENTATION: The LipiDisease webserver can be freely accessed at http://cbdm-01.zdv.uni-mainz.de:3838/piyusmor/LipiDisease/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-08-06 /pmc/articles/PMC8686672/ /pubmed/34358314 http://dx.doi.org/10.1093/bioinformatics/btab559 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Applications Notes More, Piyush Bindila, Laura Wild, Philipp Andrade-Navarro, Miguel Fontaine, Jean-Fred LipiDisease: associate lipids to diseases using literature mining |
title | LipiDisease: associate lipids to diseases using literature mining |
title_full | LipiDisease: associate lipids to diseases using literature mining |
title_fullStr | LipiDisease: associate lipids to diseases using literature mining |
title_full_unstemmed | LipiDisease: associate lipids to diseases using literature mining |
title_short | LipiDisease: associate lipids to diseases using literature mining |
title_sort | lipidisease: associate lipids to diseases using literature mining |
topic | Applications Notes |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8686672/ https://www.ncbi.nlm.nih.gov/pubmed/34358314 http://dx.doi.org/10.1093/bioinformatics/btab559 |
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