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Discovering disease-disease associations by fusing systems-level molecular data
The advent of genome-scale genetic and genomic studies allows new insight into disease classification. Recently, a shift was made from linking diseases simply based on their shared genes towards systems-level integration of molecular data. Here, we aim to find relationships between diseases based on...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3828568/ https://www.ncbi.nlm.nih.gov/pubmed/24232732 http://dx.doi.org/10.1038/srep03202 |
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author | Žitnik, Marinka Janjić, Vuk Larminie, Chris Zupan, Blaž Pržulj, Nataša |
author_facet | Žitnik, Marinka Janjić, Vuk Larminie, Chris Zupan, Blaž Pržulj, Nataša |
author_sort | Žitnik, Marinka |
collection | PubMed |
description | The advent of genome-scale genetic and genomic studies allows new insight into disease classification. Recently, a shift was made from linking diseases simply based on their shared genes towards systems-level integration of molecular data. Here, we aim to find relationships between diseases based on evidence from fusing all available molecular interaction and ontology data. We propose a multi-level hierarchy of disease classes that significantly overlaps with existing disease classification. In it, we find 14 disease-disease associations currently not present in Disease Ontology and provide evidence for their relationships through comorbidity data and literature curation. Interestingly, even though the number of known human genetic interactions is currently very small, we find they are the most important predictor of a link between diseases. Finally, we show that omission of any one of the included data sources reduces prediction quality, further highlighting the importance in the paradigm shift towards systems-level data fusion. |
format | Online Article Text |
id | pubmed-3828568 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-38285682013-11-15 Discovering disease-disease associations by fusing systems-level molecular data Žitnik, Marinka Janjić, Vuk Larminie, Chris Zupan, Blaž Pržulj, Nataša Sci Rep Article The advent of genome-scale genetic and genomic studies allows new insight into disease classification. Recently, a shift was made from linking diseases simply based on their shared genes towards systems-level integration of molecular data. Here, we aim to find relationships between diseases based on evidence from fusing all available molecular interaction and ontology data. We propose a multi-level hierarchy of disease classes that significantly overlaps with existing disease classification. In it, we find 14 disease-disease associations currently not present in Disease Ontology and provide evidence for their relationships through comorbidity data and literature curation. Interestingly, even though the number of known human genetic interactions is currently very small, we find they are the most important predictor of a link between diseases. Finally, we show that omission of any one of the included data sources reduces prediction quality, further highlighting the importance in the paradigm shift towards systems-level data fusion. Nature Publishing Group 2013-11-15 /pmc/articles/PMC3828568/ /pubmed/24232732 http://dx.doi.org/10.1038/srep03202 Text en Copyright © 2013, Macmillan Publishers Limited. All rights reserved http://creativecommons.org/licenses/by-nc-sa/3.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-ShareALike 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ |
spellingShingle | Article Žitnik, Marinka Janjić, Vuk Larminie, Chris Zupan, Blaž Pržulj, Nataša Discovering disease-disease associations by fusing systems-level molecular data |
title | Discovering disease-disease associations by fusing systems-level molecular data |
title_full | Discovering disease-disease associations by fusing systems-level molecular data |
title_fullStr | Discovering disease-disease associations by fusing systems-level molecular data |
title_full_unstemmed | Discovering disease-disease associations by fusing systems-level molecular data |
title_short | Discovering disease-disease associations by fusing systems-level molecular data |
title_sort | discovering disease-disease associations by fusing systems-level molecular data |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3828568/ https://www.ncbi.nlm.nih.gov/pubmed/24232732 http://dx.doi.org/10.1038/srep03202 |
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