Journal
FEBS LETTERS
Volume 584, Issue 16, Pages 3635-3643Publisher
WILEY
DOI: 10.1016/j.febslet.2010.07.038
Keywords
Disease phenotype; Text mining; Phenotype network; Gene functional module; Genetic origin
Funding
- National Natural Science Foundation of China [30871394, 30370798, 30571034]
- National High Tech Development Project of China
- 863 Program [2007AA02Z329]
- National Basic Research Program of China
- 973 Program [2008CB517302]
- Educational Foundation of Heilongjiang Province [11541298]
- National Science Foundation of Heilongjiang Province [JC200711, ZD200816-01, ZJG0501, GB03C602-4]
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Currently, some efforts have been devoted to the text analysis of disease phenotype data, and their results indicated that similar disease phenotypes arise from functionally related genes. These related genes work together, as a functional module, to perform a desired cellular function. We constructed a text-based human disease phenotype network and detected 82 disease-specific gene functional modules, each corresponding to a different phenotype cluster, by means of graph-based clustering and mapping from disease phenotype to gene. Since genes in such gene functional modules are functionally related and cause clinically similar diseases, they may share common genetic origin of their associated disease phenotypes. We believe the investigation may facilitate the ultimate understanding of the common pathophysiologic basis of associated diseases. (C) 2010 Federation of European Biochemical Societies. Published by Elsevier B. V. All rights reserved.
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