期刊
PLOS ONE
卷 9, 期 9, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0107202
关键词
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资金
- National Basic Research Program of China [2011CB510102, 2011CB510101]
- National Natural Science Foundation of China [31371335, 61202021, 61373028, 11371008, 81030015]
- Innovation Program of Shanghai Municipal Education Commission [12ZZ087, 12YZ120]
- Shanghai Educational Development Foundation [12CG55]
- First-class Discipline of Universities in Shanghai
Cancer is a serious disease that causes many deaths every year. We urgently need to design effective treatments to cure this disease. Tumor suppressor genes (TSGs) are a type of gene that can protect cells from becoming cancerous. In view of this, correct identification of TSGs is an alternative method for identifying effective cancer therapies. In this study, we performed gene ontology (GO) and pathway enrichment analysis of the TSGs and non-TSGs. Some popular feature selection methods, including minimum redundancy maximum relevance (mRMR) and incremental feature selection (IFS), were employed to analyze the enrichment features. Accordingly, some GO terms and KEGG pathways, such as biological adhesion, cell cycle control, genomic stability maintenance and cell death regulation, were extracted, which are important factors for identifying TSGs. We hope these findings can help in building effective prediction methods for identifying TSGs and thereby, promoting the discovery of effective cancer treatments.
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