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 …