Text mining and network analysis to find functional associations of genes in high altitude diseases. (August 2018)

• Record Type: Journal Article
• Authors: Bhasuran, Balu; Subramanian, Devika; Natarajan, Jeyakumar
• Is Part Of: Computational biology and chemistry. Volume 75(2018)
• Page Start: 101
• Page End: 110
• Publication Date: 2018-08
• Subjects: Text mining -- Gene co-occurrence -- Network analysis -- High altitude diseases; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2018.05.002
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: Integration of Text Mining and Network Analysis to explore functional association among genes involved in High Altitude Diseases. Ranked gene pairs using co-occurrence frequency from biomedical literature set of high altitude diseases. Generated gene-gene association network using statistical measures to explore potential relationships. Probable novel and existing relations of HAD-associated genes have been generated from the study. Abstract: Background and objectives: Travel to elevations above 2500 m is associated with the risk of developing one or more forms of acute altitude illness such as acute mountain sickness (AMS), high altitude cerebral edema (HACE) or high altitude pulmonary edema (HAPE). Our work aims to identify the functional association of genes involved in high altitude diseases. Method: In this work we identified the gene networks responsible for high altitude diseases by using the principle of gene co-occurrence statistics from literature and network analysis. First, we mined the literature data from PubMed on high-altitude diseases, and extracted the co-occurring gene pairs. Next, based on their co-occurrence frequency, gene pairs were ranked. Finally, a gene association network was created using statistical measures to explore potential relationships. Results: Network analysis results revealed that EPO, ACE, IL6 and TNF are the top five genes that were found to co-occur with 20 or more genes, while the association between EPAS1 and EGLN1 genes is strongly substantiated. Conclusion: The network constructed from this study proposes a large number of genes that work in-toto in high altitude conditions. Overall, the result provides a good reference for further study of the genetic relationships in high altitude diseases.