기초과학연구원 의생명수학그룹
Abstract Mathematical models of biological systems, including neurons, often feature components that evolve on very different timescales. Mathematical analysis of these multi-timescale systems can be greatly simplified by partitioning them …
We will discuss about “Exact solution of a three-stage model of stochastic gene expression including cell-cycle dynamics”, Wang, Yiling, et al., bioRxiv (2023): 2023-08. Abstract The classical three-stage model of …
We will discuss about “Antithetic proportional-integral feedback for reduced variance and improved control performance of stochastic reaction networks ”,Briat, Corentin, Ankit Gupta, and Mustafa Khammash., Journal of The Royal Society …
Abstract: Typically, the mathematical description of reaction networks involves a system of parameter-dependent ordinary differential equations. Generally, one is interested in the qualitative and quantitative behavior of solutions in various …
We will discuss about “A data-driven approach for timescale decomposition of biochemical reaction networks”, Amir Akbari, Zachary B. Haiman, Bernhard O. Palsson, bioRxiv (2023) Abstract Understanding the dynamics of biological …
We will discuss about “Power spectral estimate for discrete data”, Nobert Marwan and Tobias Braun, Chaos (2023). Abstract The identification of cycles in periodic signals is a ubiquitous problem …
Abstract: Almost all biological systems possess the ability to gather environmental information and modulate their behaviors to adaptively respond to changing environments. While animals excel at sensing odors, even simple …
We will discuss about "AutoScore:A Machine Learning–Based Automatic Clinical Score Generator and Its Application to Mortality Prediction Using Electronic Health Records", Xie, Feng, et al., JMIR medical informatics 8.10 (2020): e21798. …
We will discuss about “Significance analysis for clustering with single-cell RNA-sequencing data”, Grabski, Isabella N., Kelly Street, and Rafael A. Irizarry., Nature Methods (2023): 1-7. Abstract Unsupervised clustering of single-cell …