计算机科学
补语(音乐)
系统生物学
功能(生物学)
计算生物学
领域(数学)
数据科学
有机体
生物
表型
基因
遗传学
数学
互补
纯数学
作者
Lorenzo Bonaguro,Jonas Schulte-Schrepping,Thomas Ulas,Anna C. Aschenbrenner,Marc Beyer,Joachim L. Schultze
出处
期刊:Nature Immunology
[Springer Nature]
日期:2022-09-22
卷期号:23 (10): 1412-1423
被引量:39
标识
DOI:10.1038/s41590-022-01309-9
摘要
The immune system is highly complex and distributed throughout an organism, with hundreds to thousands of cell states existing in parallel with diverse molecular pathways interacting in a highly dynamic and coordinated fashion. Although the characterization of individual genes and molecules is of the utmost importance for understanding immune-system function, high-throughput, high-resolution omics technologies combined with sophisticated computational modeling and machine-learning approaches are creating opportunities to complement standard immunological methods with new insights into immune-system dynamics. Like systems immunology itself, immunology researchers must take advantage of these technologies and form their own diverse networks, connecting with researchers from other disciplines. This Review is an introduction and 'how-to guide' for immunologists with no particular experience in the field of omics but with the intention to learn about and apply these systems-level approaches, and for immunologists who want to make the most of interdisciplinary networks.
科研通智能强力驱动
Strongly Powered by AbleSci AI