PMTDS: a computational method based on genetic interaction networks for Precision Medicine Target-Drug Selection in cancer
作者: Varshini VasudevarajaJamie RenbargerRidhhi Girish ShahGarrett KinnebrewMurray KorcLimei WangYang HuoEnze LiuLang LiLijun Cheng
作者单位: 1Ohio State University
2Indiana University
刊名: Quantitative Biology, 2017, Vol.5 (4), pp.380-394
来源数据库: Springer Nature Journal
DOI: 10.1007/s40484-017-0126-1
关键词: Precision medicineDrug targetAlgorithmPancreatic adenocarcinomaBiological pathwayCancer
原始语种摘要: Precision medicine attempts to tailor the right therapy for the right patient. Recent progress in large-scale collection of patents’ tumor molecular profiles in The Cancer Genome Atlas (TCGA) provides a foundation for systematic discovery of potential drug targets specific to different types of cancer. However, we still lack powerful computational methods to effectively integrate multiple omics data and protein-protein interaction network technology for an optimum target and drug recommendation for an individual patient.
全文获取路径: Springer Nature  (合作)

  • medicine 
  • computational 计算的
  • collection 收集
  • adenocarcinoma 腺癌
  • interaction 相互酌
  • protein 蛋白质
  • effectively 有效地
  • pathway 轨道
  • patient 有耐性的
  • potential