生物标志物发现
计算生物学
代谢组学
生物标志物
个性化医疗
生物信息学
仿形(计算机编程)
系统生物学
转录组
医学
生物
癌症
作者
Michael Olivier,Reto Asmis,Gregory A. Hawkins,Timothy D. Howard,Laura A. Cox
摘要
Recent advances in omics technologies have led to unprecedented efforts characterizing the molecular changes that underlie the development and progression of a wide array of complex human diseases, including cancer. As a result, multi-omics analyses—which take advantage of these technologies in genomics, transcriptomics, epigenomics, proteomics, metabolomics, and other omics areas—have been proposed and heralded as the key to advancing precision medicine in the clinic. In the field of precision oncology, genomics approaches, and, more recently, other omics analyses have helped reveal several key mechanisms in cancer development, treatment resistance, and recurrence risk, and several of these findings have been implemented in clinical oncology to help guide treatment decisions. However, truly integrated multi-omics analyses have not been applied widely, preventing further advances in precision medicine. Additional efforts are needed to develop the analytical infrastructure necessary to generate, analyze, and annotate multi-omics data effectively to inform precision medicine-based decision-making.
科研通智能强力驱动
Strongly Powered by AbleSci AI