We will discuss about “Balanced truncation for model reduction of biological oscillators”, Padoan et al., Biological Cybernetics, 2021 Model reduction is a central problem in mathematical biology. Reduced order models enable modeling of a biological system at different levels of complexity and the quantitative analysis of its properties, like sensitivity to parameter variations and resilience …

We will discuss about “Filtering and inference for stochastic oscillators with distributed delays”, Calderazzo et al., Bioinformatics, 2018 at the Journal Club Motivation The time evolution of molecular species involved in biochemical reaction networks often arises from complex stochastic processes involving many species and reaction events. Inference for such systems is profoundly challenged by the …

We will discuss about “Detecting and quantifying causal associations in large nonlinear time series datasets”, Runge et al., Science Advances, 2019 Identifying causal relationships and quantifying their strength from observational time series data are key problems in disciplines dealing with complex dynamical systems such as the Earth system or the human body. Data-driven causal inference …

We will discuss about “Solving Singular Control Problems in Mathematical Biology, Using PASA”, Atkins et al., arXiv, 2020 In this paper, we will demonstrate how to use a nonlinear polyhedral constrained optimization solver called the Polyhedral Active Set Algorithm (PASA) for solving a general singular control problem. We present methods of discretizing a general optimal …