基本信息
浏览量:7
职业迁徙
个人简介
As part of the Engineering Biology Team, David's research is aimed at developing the measurement tools and theoretical approaches necessary for quantitative prediction and control of complex biosystem behavior. He is particularly interested in predictive approaches based on understanding the emergent behavior of biosystems rather than detailed modeling of the molecular mechanisms underlying that behavior. For example, if a biosystem is evolutionarily optimized to perform some function, then, if you can precisely understand and define what "optimized" means, you can calculate the optimal behavior and use it as a prediction – without any specific reference to the underlying mechanisms. This leads to numerous questions which David's research is aimed to address, such as: What are the appropriate "fitness functions" to be optimized? How close are the measureable behaviors to the predicted optimum for real biosystems? And how does this depend on the environmental context that the biosystem is in? When behaviors are not optimal, does a biosystem adapt toward an optimum? And what are the dynamics of that adaptation? Because of the close mathematical connection between growth rates and efficiency of information usage, David's work is focused on theoretical and experimental approaches to understand the adaptation, evolution, and optimization of information flow in complex biological systems, and on the use of that understanding to develop design rules for more robust engineering of biological function.
研究兴趣
论文共 185 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
PloS oneno. 10 (2023): e0292401-e0292401
Drew S. Tack,Peter D. Tonner,Abe Pressman, Nathanael D. Olson,Sasha F Levy, Eugenia F. Romantseva,Nina Alperovich,Olga Vasilyeva,David Ross
crossref(2022)
Cell-Free Gene Expression (2022)
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn