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Embedding computation in biochemical environments incompatible with traditional electronics is expected to have wide-ranging impact in synthetic biology, medicine, nanofabrication and other fields. Natural biochemical systems are typically…

Machine Learning · Computer Science 2022-06-15 Marko Vasic , Cameron Chalk , Austin Luchsinger , Sarfraz Khurshid , David Soloveichik

Chemical reaction networks (CRNs) are a standard formalism used in chemistry and biology to reason about the dynamics of molecular interaction networks. In their interpretation by ordinary differential equations, CRNs provide a…

Quantitative Methods · Quantitative Biology 2020-07-28 Mathieu Hemery , François Fages , Sylvain Soliman

Graph transformation systems have the potential to be realistic models of chemistry, provided a comprehensive collection of reaction rules can be extracted from the body of chemical knowledge. A first key step for rule learning is the…

Discrete Mathematics · Computer Science 2016-04-22 Christoph Flamm , Daniel Merkle , Peter F. Stadler , Uffe Thorsen

Retrosynthesis is one of the fundamental problems in organic chemistry. The task is to identify reactants that can be used to synthesize a specified product molecule. Recently, computer-aided retrosynthesis is finding renewed interest from…

Machine Learning · Computer Science 2020-01-07 Hanjun Dai , Chengtao Li , Connor W. Coley , Bo Dai , Le Song

We present a differentiable formulation of abstract chemical reaction networks (CRNs) that can be trained to solve a variety of computational tasks. Chemical reaction networks are one of the most fundamental computational substrates used by…

Molecular Networks · Quantitative Biology 2023-02-07 Alexander Mordvintsev , Ettore Randazzo , Eyvind Niklasson

Chemical reaction networks (CRNs) are fundamental computational models used to study the behavior of chemical reactions in well-mixed solutions. They have been used extensively to model a broad range of biological systems, and are primarily…

Molecular Networks · Quantitative Biology 2021-05-13 J. N. Mueller , J. N. Corcoran

The purpose of this review is to introduce the reader to graph kernels and the corresponding literature, with an emphasis on those with direct application to chemoinformatics. Graph kernels are functions that allow for the inference of…

Machine Learning · Statistics 2022-08-29 James Young

Prediction of complete step-by-step chemical reaction mechanisms (CRMs) remains a major challenge. Whereas the traditional approaches in CRM tasks rely on expert-driven experiments or costly quantum chemical computations, contemporary deep…

Chemical Physics · Physics 2025-12-11 Manajit Das , Ajnabiul Hoque , Mayank Baranwal , Raghavan B. Sunoj

Chemical reaction networks (CRNs) model systems where molecules interact according to a finite set of reactions such as $A + B \to C$, representing that if a molecule of $A$ and $B$ collide, they disappear and a molecule of $C$ is produced.…

Computational Complexity · Computer Science 2026-01-21 David Doty , Ben Heckmann

Automated and high-throughput quantum chemical investigations into chemical processes have become feasible in great detail and broad scope. This results in an increase in complexity of the tasks and in the amount of generated data. An…

Understanding and predicting interface diffusion phenomena in materials is crucial for various industrial applications, including semiconductor manufacturing, battery technology, and catalysis. In this study, we propose a novel approach…

Materials Science · Physics 2025-01-13 Zirui Zhao , Hai-Feng Li

This paper studies the (discrete) \emph{chemical reaction network (CRN)} computational model that emerged in the last two decades as an abstraction for molecular programming. The correctness of CRN protocols is typically established under…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-07-04 Anne Condon , Yuval Emek , Noga Harlev

Chemical kinetics plays an important role in governing the thermal evolution in reactive flows problems. The possible interactions between chemical species increase drastically with the number of species considered in the system. Various…

Instrumentation and Methods for Astrophysics · Physics 2022-07-18 Kwok Sun Tang , Matthew Turk

Graph transformation formalisms have proven to be suitable tools for the modelling of chemical reactions. They are well established in theoretical studies and increasingly also in practical applications in chemistry. The latter is made…

Discrete Mathematics · Computer Science 2022-08-29 Jakob L. Andersen , Rolf Fagerberg , Juri Kolčák , Christophe V. F. P. Laurent , Daniel Merkle , Nikolai Nøjgaard

The Chemical Reaction Network (CRN) is a well-studied model that describes the interaction of molecules in well-mixed solutions. In 2014, Qian and Winfree [22] proposed the abstract surface chemical reaction network model (sCRN), which…

Computational Complexity · Computer Science 2024-06-14 Yi-Xuan Lee , Ho-Lin Chen

Stochastic chemical reaction networks (CRNs) are complex systems which combine the features of concurrent transformation of multiple variables in each elementary reaction event, and nonlinear relations between states and their rates of…

Chemical Physics · Physics 2017-12-06 Eric Smith , Supriya Krishnamurthy

Investigating a reactive chemical system with automated reaction network exploration algorithms provides a more detailed picture of its chemical mechanism than what would be accessible by manual investigation. In general, exploration…

Chemical Physics · Physics 2023-04-14 Moritz Bensberg , Markus Reiher

The evolution of chemical reaction networks is often analyzed through kinetic models and energy landscapes, but these approaches fail to capture the deeper structural constraints governing complexity growth. In chemical reaction networks,…

Molecular Networks · Quantitative Biology 2025-04-22 Anderson M. Rodriguez

The dynamics of a chemical reaction network (CRN) is often modelled under the assumption of mass action kinetics by a system of ordinary differential equations (ODEs) with polynomial right-hand sides that describe the time evolution of…

Dynamical Systems · Mathematics 2023-01-05 Radek Erban , Hye-Won Kang

Direct numerical simulations of turbulent reacting flows involving millions of grid points and detailed chemical mechanisms with hundreds of species and thousands of reactions are computationally prohibitive. To address this challenge, we…

Machine Learning · Computer Science 2026-03-25 Manuru Nithin Padiyar , Priyabrat Dash , Konduri Aditya