生物
计算生物学
吞吐量
肿瘤异质性
计算模型
数据科学
精确肿瘤学
癌症
计算机科学
人工智能
遗传学
电信
无线
作者
Leonie Kolmar,Alexis Autour,Xiaoli Ma,Blandine Vergier,Federica Eduati,Christoph A. Merten
标识
DOI:10.1016/j.tcb.2022.04.008
摘要
Engineering and computational advances have opened many new avenues in cancer research, particularly when being exploited in interdisciplinary approaches. For example, the combination of microfluidics, novel sequencing technologies, and computational analyses has been crucial to enable single-cell assays, giving a detailed picture of tumor heterogeneity for the very first time. In a similar way, these 'tech' disciplines have been elementary for generating large data sets in multidimensional cancer 'omics' approaches, cell-cell interaction screens, 3D tumor models, and tissue level analyses. In this review we summarize the most important technology and computational developments that have been or will be instrumental for transitioning classical cancer research to a large data-driven, high-throughput, high-content discipline across all biological scales.
科研通智能强力驱动
Strongly Powered by AbleSci AI