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Gene Ontology and KEGG Enrichment Analyses of Genes Related to Age-Related Macular Degeneration
Author(s) -
Jian Zhang,
Zhihao Xing,
Mingming Ma,
Ning Wang,
YuDong Cai,
Lei Chen,
Xun Xu
Publication year - 2014
Publication title -
biomed research international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.772
H-Index - 126
eISSN - 2314-6141
pISSN - 2314-6133
DOI - 10.1155/2014/450386
Subject(s) - kegg , gene ontology , gene , computational biology , biomedicine , ontology , biology , computer science , bioinformatics , genetics , gene expression , philosophy , epistemology
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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