Journal Club

We will discuss about “DeepCME: A deep learning framework for solving the Chemical Master Equation,” Gupta et al., bioRxiv, 2021 Stochastic models of biomolecular reaction networks are commonly employed in systems and synthetic biology to study the effects of stochastic fluctuations emanating from reactions involving species with low copy-numbers. For such models, the Kolmogorov’s forward …

We will discuss about “Modeling Cell-to-Cell Communication Networks Using Response-Time Distributions”, Thurley et al., Cell Systems, 2021 Abstract: Cell-to-cell communication networks have critical roles in coordinating diverse organismal processes, such as tissue development or immune cell response. However, compared with intracellular signal transduction networks, the function and engineering principles of cell-to-cell communication networks are far …

We will discuss about “Parameter Estimation in a Model of the Human Circadian Pacemaker Using a Particle Filter”, Bonarius et. al., IEEE Trans. Biomed. Eng., 2021 Abstract Objective: In the near future, real-time estimation of peoples unique, precise circadian clock state has the potential to improve the efficacy of medical treatments and improve human performance …

We will discuss about “Stochastic reaction networks in dynamic compartment populations”, Duso and Zechner, PNAS, 2020 Abstract: Compartmentalization of biochemical processes underlies all biological systems, from the organelle to the tissue scale. Theoretical models to study the interplay between noisy reaction dynamics and compartmentalization are sparse, and typically very challenging to analyze computationally. Recent studies …

We will discuss about “Frequency Modulation of Transcriptional Bursting Enables Sensitive and Rapid Gene Regulation”, Li et. al., Cell Systems, 2018 Abstract Gene regulation is a complex non-equilibrium process. Here, we show that quantitating the temporal regulation of key gene states (transcriptionally inactive, active, and refractory) provides a parsimonious framework for analyzing gene regulation. Our …

We will discuss about “TimeCycle: Topology Inspired MEthod for the Detection of Cycling Transcripts in Circadian Time-Series Data”, Ness-Cohn and Braun, Bioinformatics, 2021 Abstract Motivation: The circadian rhythm drives the oscillatory expression of thousands of genes across all tissues. The recent revolution in high-throughput transcriptomics, coupled with the significant implicatins of the circadian clock for …

We will discuss about "Cellular signaling beyond the Wiener-Kolmogorov limit", Weisenberger et al., bioRxiv, 2021 Abstract: Accurate propagation of signals through stochastic biochemical networks involves significant expenditure of cellular resources. The same is true for regulatory mechanisms that suppress fluctuations in biomolecular populations. Wiener-Kolmogorov (WK) optimal noise filter theory, originally developed for engineering problems, has …

We will discuss about "Machine learning of stochastic gene network phenotypes", Park et al., bioRxiv, 2019 Abstract: A recurrent challenge in biology is the development of predictive quantitative models because most molecular and cellular parameters have unknown values and realistic models are analytically intractable. While the dynamics of the system can be analyzed via computer …

We will discuss about “Nonlinear delay differential equations and their application to modeling biological network motifs”, Glass et al., Nature Communications, 2021 Abstract: Biological regulatory systems, such as cell signaling networks, nervous systems and ecological webs, consist of complex dynamical interactions among many components. Network motif models focus on small sub-networks to provide quantitative insight …

We will discuss about “The Oscillation Amplitude, Not the Frequency of Cytosolic Calcium, Regulates Apoptosis Induction ”, Qi et al., iScience, 2020 Abstract: Although a rising concentration of cytosolic Ca2+ has long been recognized as an essential signal for apoptosis, the dynamical mechanisms by which Ca2+ regulates apoptosis are not clear yet. To address this, we constructed …

We will discuss about “A spatio-temporal model to reveal oscillator phenotypes in molecular clocks: Parameter estimation elucidates circadian gene transcription dynamics in single-cells”, Unosson et al., bioRxiv, 2021 We propose a stochastic distributed delay model together with a Markov random field prior and a measurement model for bioluminescence-reporting to analyse spatiotemporal gene expression in intact …

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 …