Mining Disease Associated Biomarker Networks from PubMed
Disease related biomarker discovery is the critical step to realize the future personalized medicine and has been an important research area.With exponential growing of biomedical knowledge deposited in PubMed database,it is now an essential step to mine PubMed for biomarker-disease associations to support the laboratory research and clinical validation.We constructed list of human diseases that are most frequently associated with biomarker in literatures by text mining.Top ranked neurology diseases were then used to extract associated genes from PubMed using context sensitive information retrieval methods.Associated genes were then integrated into pathways and subject to network biomarker analysis.Our approach identifies both known and potential biomarkers for 3 neurodegenerative diseases.
biomarker disease-gene association semantic text mining biological network
Zhong Huang
School of Information Science and Technology Drexel University Philadelphia, USA
国际会议
7th International Conference on Systems Biology(第7届计算系统生物学国际研讨会)(ISB2013)
安徽黄山
英文
15-18
2013-08-22（万方平台首次上网日期，不代表论文的发表时间）