共 55 条
Viral evolution: beyond drift and shift
被引:18
作者:

Greenbaum, Benjamin D.
论文数: 0 引用数: 0
h-index: 0
机构:
Tisch Canc Inst, Dept Med, New York, NY 10029 USA
Tisch Canc Inst, Dept Pathol, New York, NY 10029 USA Tisch Canc Inst, Dept Med, New York, NY 10029 USA

Ghedin, Elodie
论文数: 0 引用数: 0
h-index: 0
机构:
NYU, Ctr Genom & Syst Biol, Dept Biol, New York, NY 10003 USA
NYU, Global Inst Publ Hlth, New York, NY 10003 USA Tisch Canc Inst, Dept Med, New York, NY 10029 USA
机构:
[1] Tisch Canc Inst, Dept Med, New York, NY 10029 USA
[2] Tisch Canc Inst, Dept Pathol, New York, NY 10029 USA
[3] NYU, Ctr Genom & Syst Biol, Dept Biol, New York, NY 10003 USA
[4] NYU, Global Inst Publ Hlth, New York, NY 10003 USA
基金:
美国国家卫生研究院;
关键词:
INFLUENZA-A;
VIRUS ATTENUATION;
RNA;
REASSORTMENT;
CPG;
RECOGNITION;
INFORMATION;
FREQUENCIES;
INFECTION;
SEQUENCES;
D O I:
10.1016/j.mib.2015.06.015
中图分类号:
Q93 [微生物学];
学科分类号:
071005 ;
100705 ;
摘要:
Technological advances have allowed aspects of viral evolution to be explored at unprecedented scales. As a consequence, new quantitative approaches are needed to investigate features of viral evolution that fall outside traditional areas of study, such as antigenic evolution. We examine three areas of viral evolution where tools from disciplines such as statistical physics, topology, and information theory have been used recently as quantitative frameworks for large-scale studies and, in some cases, suggest a novel theoretical approach to a problem. Ongoing interaction among these disciplines with biology is necessary so that experimental researchers can determine which quantitative tools are right for them and quantitative researchers can learn which aspects of viral evolution can be understood and advanced with their approaches.
引用
收藏
页码:109 / 115
页数:7
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