小桶
致癌物
计算生物学
计算机科学
癌变
生物信息学
癌症
生物
基因本体论
遗传学
基因
基因表达
出处
期刊:Combinatorial Chemistry & High Throughput Screening
[Bentham Science]
日期:2018-02-13
卷期号:20 (10): 861-871
被引量:29
标识
DOI:10.2174/1386207321666171218120133
摘要
Aim and Objective: Cancer is one of the serious diseases that cause several human deaths every year. Up to now, we have spent lots of time and money to investigate this disease, thereby designing effective treatments. Previous studies mainly focus on studying genetic background of different subtypes of cancer and neglect another important factor, i.e. environmental factor. Carcinogenic chemical is one of the types of environmental factor; the exposure of such chemical may definitely initiate and promote the tumorigenesis. In this study, we tried to partly describe the differences between carcinogenic and non-carcinogenic chemicals using gene ontology (GO) terms and KEGG pathways. Material and Methods: The carcinogenic and non-carcinogenic chemicals that were retrieved from Carcinogenic Potency Database (CPDB) were encoded into numeric vectors using the enrichment theories of GO terms and KEGG pathways. Then, the minimal redundancy maximal relevance (mRMR) method was adopted to analyze all the features, resulting in some important GO terms and KEGG pathways. Results and Conclusion: The extensive analysis of the identified GO terms and KEGG pathways indicates that they all play roles during tumorigenesis, inducing that they can be the key indicator for the identification of carcinogenic chemicals. Keywords: Carcinogenic chemical, non-carcinogenic chemical, enrichment score, GO term, KEGG pathway, minimal redundancy maximal relevance.
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