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题目:: Establishing reliable miRNA-cancer association network based on text-mining method.
作者:: Li(Lun),Hu(Xingchi),Yang(Zhaowan),Jia(Zhenyu),Fang(Ming),Zhang(Libin),Zhou(Yanhong)
状态:: 发布时间2014-06-04 , 更新时间 2015-08-05
期刊:: Comput Math Methods Med
摘要:: Associating microRNAs (miRNAs) with cancers is an important step of understanding the mechanisms of cancer pathogenesis and finding novel biomarkers for cancer therapies. In this study, we constructed a miRNA-cancer association network (miCancerna) based on more than 1,000 miRNA-cancer associations detected from millions of abstracts with the text-mining method, including 226 miRNA families and 20 common cancers. We further prioritized cancer-related miRNAs at the network level with the random-walk algorithm, achieving a relatively higher performance than previous miRNA disease networks. Finally, we examined the top 5 candidate miRNAs for each kind of cancer and found that 71% of them are confirmed experimentally. miCancerna would be an alternative resource for the cancer-related miRNA identification.
语言:: eng
DOI:

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