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Brussels, Belgium Belgium
Dec. 10, 2012 to Dec. 10, 2012
ISBN: 978-1-4673-5164-5
pp: 94-98
An important task of aging research is to find genes that regulate lifespan. Wet-lab identification of aging genes is tedious and labor-intensive activity. Developing an algorithm to predict aging genes will be greatly helpful. In this paper, we systematically analyzed topological features of proteins encoded by Drosophila melanogaster aging genes versus those encoded by non-aging genes in protein-protein interaction (PPI) network and found that aging genes are characterized by several network topological features such as higher in degrees. Based on these features, an algorithm was developed to detect aging genes genome wide. With a posterior probability score describing possible involvement in aging higher than 0.7, 54 novel aging genes were predicted. Evidence supporting our prediction can be found.
Aging, Proteins, Bioinformatics, Humans, Genomics, Diseases, Support vector machines, prediction, aging genes, algorithm
Xin Song, Yuan-Chun Zhou, Kai Feng, Yan-Hui Li, Jian-Hui Li, "Discovering Aging-Genes by Topological Features in Drosophila melanogaster Protein-Protein Interaction Network", ICDMW, 2012, 2013 IEEE 13th International Conference on Data Mining Workshops, 2013 IEEE 13th International Conference on Data Mining Workshops 2012, pp. 94-98, doi:10.1109/ICDMW.2012.30
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