Details

Autor(en) / Beteiligte

• Soliman, Maha
• Nasraoui, Olfa
• Cooper, Nigel G.F

Titel

Analysis and visualization of a literature-mined glaucoma gene interaction network

Ist Teil von

• 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2016, p.669-676

Ort / Verlag

IEEE

Erscheinungsjahr

2016

Quelle

ACM Digital Library

Beschreibungen/Notizen

• Glaucoma is a silent eye disease that steals sight without warning and it is the second leading cause of blindness worldwide. It cannot be cured but it can be controlled. A gene network analysis to understand the cross talk between glaucoma networks of genes could contribute to better understanding and treatment of the disease. In this paper, we extend our previous text mining and network analysis research for extraction of a more comprehensive glaucoma interaction network from PubMed Central articles. After text mining of the PubMed Central literature to extract potential sentences bearing associations between glaucoma genes in the literature, the mined associations are used to construct a glaucoma gene interaction network and a network analysis is applied to understand the building structure of the network. The network analysis reveals a succinct network composed of five distinct clusters associated with seven benchmark glaucoma biomarkers. The knowledge that can be extracted from such a network could provide a useful summative knowledge base to complement other forms of clinical information related to this disease that affects many diagnosed individuals worldwide.