The Gillespie algorithm is commonly used to simulate and analyze complex chemical reaction networks. Here, we leverage recent breakthroughs in deep learning to develop a fully differentiable variant of the Gillespie algorithm. The differentiable Gillespie algorithm (DGA) approximates discontinuous operations in the exact Gillespie algorithm using smooth functions, allowing for the calculation of gradients using backpropagation. The DGA can be used to quickly and accurately learn kinetic parameters using gradient descent and design biochemical networks with desired properties. As an illustration, we apply the DGA to study stochastic models of gene promoters. We show that the DGA can be used to: (i) successfully learn kinetic parameters from experimental measurements of mRNA expression levels from two distinct promoters and (ii) design nonequilibrium promoter architectures with desired input-output relationships. These examples illustrate the utility of the DGA for analyzing stochastic chemical kinetics, including a wide variety of problems of interest to synthetic and systems biology.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11469443 | PMC |
Publication Analysis
Top Keywords
Similar Publications
An evolutionary game theory for event-driven ecological population dynamics.
Theory Biosci
January 2025
Faculty of Science and Engineering, Department of Biosciences, Swansea University, Singleton Park, Swansea, SA2 8PP, UK.
Despite being a powerful tool to model ecological interactions, traditional evolutionary game theory can still be largely improved in the context of population dynamics. One of the current challenges is to devise a cohesive theoretical framework for ecological games with density-dependent (or concentration-dependent) evolution, especially one defined by individual-level events. In this work, I use the notation of reaction networks as a foundation to propose a framework and show that classic two-strategy games are a particular case of the theory.
View Article and Find Full Text PDFThe dynamics of prion spreading is governed by the interplay between the non-linearities of tissue response and replication kinetics.
iScience
December 2024
Université Paris-Saclay, INRAe, UVSQ, VIM, 78350 Jouy-en-Josas, France.
Prion diseases, or transmissible spongiform encephalopathies (TSEs), are neurodegenerative disorders caused by the accumulation of misfolded conformers (PrP) of the cellular prion protein (PrP). During the pathogenesis, the PrP seeds disseminate in the central nervous system and convert PrP leading to the formation of insoluble assemblies. As for conventional infectious diseases, variations in the clinical manifestation define a specific prion strain which correspond to different PrP structures.
View Article and Find Full Text PDFInherent stochasticity, noise and limits of detection in continuous and time-gated fluorescence systems.
PLoS One
December 2024
Department of Electrical Engineering, Stanford University, Stanford, California, United States of America.
Article Synopsis
- A model was developed to analyze the noise and randomness in fluorescence signals under continuous wave (CW) and time-gated (TG) conditions, focusing on how different excitation photon flux affects fluorophore emission.
- Both ensemble and stochastic models were validated through Monte Carlo molecular dynamics simulations using the Gillespie algorithm, showing their effectiveness in capturing the dynamics of fluorescence.
- The study explores the implications of the model for designing biomolecular fluorescence detection systems, emphasizing trade-offs related to signal-to-noise ratios and detection limits as systems shrink to micro- and nano-scales, highlighting the advantages of TG systems in terms of cost and complexity when suitable fluorophores are used.
A mathematical model of plasmin-mediated fibrinolysis of single fibrin fibers.
PLoS Comput Biol
December 2024
Department of Mathematics and Statistics, University of Central Oklahoma, Edmond, Oklahoma, United States of America.
Fibrinolysis, the plasmin-mediated degradation of the fibrin mesh that stabilizes blood clots, is an important physiological process, and understanding mechanisms underlying lysis is critical for improved stroke treatment. Experimentalists are now able to study lysis on the scale of single fibrin fibers, but mathematical models of lysis continue to focus mostly on fibrin network degradation. Experiments have shown that while some degradation occurs along the length of a fiber, ultimately the fiber is cleaved at a single location.
View Article and Find Full Text PDFDiscovery of 6α-Thiazolylcarboxamidonaltrexamine Derivative (NTZ) as a Potent and Central Nervous System Penetrant Opioid Receptor Modulator with Drug-like Properties for Potential Treatment of Opioid Use Disorder.
ACS Pharmacol Transl Sci
December 2024
Department of Medicinal Chemistry, School of Pharmacy, Virginia Commonwealth University, 800 E Leigh Street, Richmond, Virginia23298, United States.
The development of highly potent and selective μ opioid receptor (MOR) modulators with favorable drug-like properties has always been a focus in the opioid domain. Our previous efforts led to the discovery of a lead compound designated as NAT, a potent centrally acting MOR modulator. However, the fact that NAT precipitated considerable withdrawal effects at higher doses largely impaired its further development.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!