We will discuss about "Chemical Organisation Theory ", Dittrich, Peter, and Pietro Speroni Di Fenizio, Bulletin of mathematical biology 69.4 (2007): 1199-1231. Abstract: Complex dynamical reaction networks consisting of many …

We will discuss about "Accuracy and limitations of extrinsic noise models to describe gene expression in growing cells", Jia, Chen, and Ramon Grima, bioRxiv (2022). Abstract: The standard model describing …

We will discuss about "Learning stable and predictive structures in kinetic systems", Niklas Pfister , Stefan Bauer, and Jonas Peters. PNAS, 2019 Abstract: Learning kinetic systems from data is one …

We will discuss about "Neural Ordinary Differential Equations", Chen, Ricky TQ, et al., Advances in neural information processing systems 31 (2018). Abstract: We introduce a new family of deep neural …

We will discuss about "Molecular convolutional neural networks with DNA regulatory circuits", Pei, Hao, et al., Nature Machine Intelligence (2022): 1-11. Abstract: Complex biomolecular circuits enabled cells with intelligent behaviour …

We will discuss about "Inferring Regulatory Networks from Expression Data Using Tree-Based Methods," Huynh-Thu et al., PLoS ONE (2010). Abstract: One of the pressing open problems of computational systems biology …

We will discuss about "Hidden Markov models for monitoring circadian rhythmicity in telemetric activity data", Huang, Qi, Journal of The Royal Society Interface 15.139 (2018): 20170885. Abstract: Wearable computing devices …

We will discuss about "Physics-informed neural networks for PDE-constrained optimization and control", Barry-Straume, Jostein, et al., arXiv preprint arXiv:2205.03377 (2022). Abstract: A fundamental problem of science is designing optimal control …