文章基本信息

标题：Discovering disease-disease associations by fusing systems-level molecular data
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作者：Marinka Žitnik ; Vuk Janjić ; Chris Larminie 等
期刊名称：Scientific Reports
电子版ISSN：2045-2322
出版年度：2013
卷号：3
DOI：10.1038/srep03202
出版社：Springer Nature
摘要：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.