Stochastic Modeling and Statistical Inference in Biology

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Guest Editor
Dr. John Fricks
School of Mathematical and Statistical Sciences, Arizona State University, USA
Email: john.fricks@asu.edu

Manuscript Topics
This special issue will present the analysis of biological systems from the mathematical perspective of stochastic processes and statistical inference.  A variety of experimental systems have benefitted from this perspective over recent years.  The study of intracellular biochemical networks, in particular, has been enriched by having researchers working at the intersection of stochastic processes theory and more traditional applied mathematics.  In addition, the ability to collect a substantial amount of biological data, especially by obtaining time series at scales ranging from molecular to cellular to whole organism has changed our capacity to link stochastic models to observations.  While a statistical link to data is not required, manuscripts of particular interest for this issue will be those that are tightly coupled to experiments and/or applications, especially if the modeling provides unique biological insights.

Paper Submission
All manuscripts will be peer-reviewed before their acceptance for publication.
The deadline for manuscript submission is December 30, 2020.

Instructions for authors
http://www.aimspress.com/news/295.html
Please submit your manuscript to online submission system
http://oeps.aimspress.com/mbe/ch/author/login.aspx

Simone Göttlich, Stephan Knapp, Dylan Weber
+ Abstract     + HTML     + PDF(2561 KB)
Zhenquan Zhang, Junhao Liang, Zihao Wang, Jiajun Zhang, Tianshou Zhou
+ Abstract     + HTML     + PDF(716 KB)
Peng Wu, Baosheng Liang, Yifan Xia, Xingwei Tong
+ Abstract     + HTML     + PDF(649 KB)
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