用于研究病原体生物学及其所致传染病的数学模型。
Mathematical models to study the biology of pathogens and the infectious diseases they cause.
作者信息
Xavier Joao B, Monk Jonathan M, Poudel Saugat, Norsigian Charles J, Sastry Anand V, Liao Chen, Bento Jose, Suchard Marc A, Arrieta-Ortiz Mario L, Peterson Eliza J R, Baliga Nitin S, Stoeger Thomas, Ruffin Felicia, Richardson Reese A K, Gao Catherine A, Horvath Thomas D, Haag Anthony M, Wu Qinglong, Savidge Tor, Yeaman Michael R
机构信息
Program for Computational and Systems Biology, Memorial Sloan-Kettering Cancer Center, New York, NY, USA.
Department of Bioengineering, UC San Diego, San Diego, CA, USA.
出版信息
iScience. 2022 Mar 15;25(4):104079. doi: 10.1016/j.isci.2022.104079. eCollection 2022 Apr 15.
Mathematical models have many applications in infectious diseases: epidemiologists use them to forecast outbreaks and design containment strategies; systems biologists use them to study complex processes sustaining pathogens, from the metabolic networks empowering microbial cells to ecological networks in the microbiome that protects its host. Here, we (1) review important models relevant to infectious diseases, (2) draw parallels among models ranging widely in scale. We end by discussing a minimal set of information for a model to promote its use by others and to enable predictions that help us better fight pathogens and the diseases they cause.
数学模型在传染病领域有诸多应用
流行病学家用它们来预测疫情爆发并设计防控策略；系统生物学家用它们来研究维持病原体生存的复杂过程，从赋予微生物细胞能量的代谢网络到保护宿主的微生物群落中的生态网络。在此，我们（1）回顾与传染病相关的重要模型，（2）对规模差异很大的模型进行比较。最后，我们讨论了一组最少的模型信息，以促进他人对模型的使用，并实现有助于我们更好地对抗病原体及其所致疾病的预测。
Zotero 插件