Journal
BIOMED RESEARCH INTERNATIONAL
Volume 2014, Issue -, Pages -Publisher
HINDAWI LTD
DOI: 10.1155/2014/450386
Keywords
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Funding
- National Basic Research Program of China [2011CB510101]
- Doctoral Innovation Fund of Shanghai Jiaotong University School of Medicine [BXJ201337, BXJ201234]
- National Natural Science Foundation of China [81100679, 81273424, 31371335, 61202021]
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Identifying disease genes is one of the most important topics in biomedicine and may facilitate studies on the mechanisms underlying disease. Age-related macular degeneration (AMD) is a serious eye disease; it typically affects older adults and results in a loss of vision due to retina damage. In this study, we attempt to develop an effective method for distinguishing AMD-related genes. Gene ontology and KEGG enrichment analyses of known AMD-related genes were performed, and a classification system was established. In detail, each gene was encoded into a vector by extracting enrichment scores of the gene set, including it and its direct neighbors in STRING, and gene ontology terms or KEGG pathways. Then certain feature-selection methods, including minimum redundancy maximum relevance and incremental feature selection, were adopted to extract key features for the classification system. As a result, 720 GO terms and 11 KEGG pathways were deemed the most important factors for predicting AMD-related genes.
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