Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
A probabilistic interpretation of precision, recall and F-score, with implication for evaluation
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
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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. And aging genes tend to be enriched in certain functions were also found. Based on these features, an algorithm was developed to detect aging genes genome wide. With a posterior probability score describing possible involvement in aging no less than 1, 1014 novel aging genes were predicted by decision trees. Evidence supporting our prediction can be found.