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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

A nut graph is a graph on at least 2 vertices whose adjacency matrix has nullity 1 and for which non-trivial kernel vectors do not contain a zero. Chemical graphs are connected, with maximum degree at most three. We present a new algorithm…

Combinatorics · Mathematics 2017-09-14 Kris Coolsaet , Patrick W. Fowler , Jan Goedgebeur

We construct an information-geometric structure for chemical thermodynamics, applicable to a wide range of chemical reaction systems including non-ideal and open systems. For this purpose, we explicitly construct dual affine coordinate…

Statistical Mechanics · Physics 2022-10-26 Naruo Ohga , Sosuke Ito

Finding the main product of a chemical reaction is one of the important problems of organic chemistry. This paper describes a method of applying a neural machine translation model to the prediction of organic chemical reactions. In order to…

Machine Learning · Computer Science 2017-01-02 Juno Nam , Jurae Kim

Biochemical processes typically involve huge numbers of individual reversible steps, each with its own dynamical rate constants. For example, kinetic proofreading processes rely upon numerous sequential reactions in order to guarantee the…

Molecular Networks · Quantitative Biology 2009-12-28 Golan Bel , Brian Munsky , Ilya Nemenman

The construction of a reaction network containing all relevant intermediates and elementary reactions is necessary for the accurate description of chemical processes. In the case of a complex chemical reaction (involving, for instance, many…

Chemical Physics · Physics 2017-12-19 Gregor N. Simm , Markus Reiher

It is useful to have complete lists of nonisomorphic chemical reaction networks (CRNs) of a given size, with or without various restrictions. One may, for example, be interested in exploring how often certain dynamical behaviours occur in…

Molecular Networks · Quantitative Biology 2017-06-01 Murad Banaji

Deep generative models have been shown powerful in generating novel molecules with desired chemical properties via their representations such as strings, trees or graphs. However, these models are limited in recommending synthetic routes…

Artificial Intelligence · Computer Science 2022-08-02 Dai Hai Nguyen , Koji Tsuda

Significant progress in the development of efficient and fast algorithms for quantum chemical calculations has been made in the past two decades. The main focus has always been the desire to be able to treat ever larger molecules or…

Chemical Physics · Physics 2012-12-18 Moritz P. Haag , Markus Reiher

A construction sequence for a graph is a listing of the elements of the graph (the set of vertices and edges) such that each edge follows both its endpoints. The construction number of the graph is the number of such sequences. We determine…

Combinatorics · Mathematics 2024-12-03 Paul C. Kainen

For decades, computational chemistry has been posited as one of the areas in which quantum computing would revolutionize. However, the algorithmic advantages that fault-tolerant quantum computers have for chemistry can be overwhelmed by…

A quantum Matter-Photonics framework is adapted to help scrutinize chemical reaction mechanisms and used to explore a process mapped from chemical tree topological model. The chemical concept of bond knitting/breaking is reformulated via…

Chemical Physics · Physics 2014-11-03 O. Tapia

One of the most promising suggested applications of quantum computing is solving classically intractable chemistry problems. This may help to answer unresolved questions about phenomena like: high temperature superconductivity, solid-state…

Quantum Physics · Physics 2020-04-08 Sam McArdle , Suguru Endo , Alan Aspuru-Guzik , Simon Benjamin , Xiao Yuan

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

Chemical reactions are a prominent feature of molecular communication (MC) systems, with no direct parallels in wireless communications. While chemical reactions may be used inside the transmitter nodes, receiver nodes or the communication…

Information Theory · Computer Science 2018-04-25 Maryam Farahnak-Ghazani , Gholamali Aminian , Mahtab Mirmohseni , Amin Gohari , Masoumeh Nasiri-Kenari

Synthetic biology is a rapidly emerging research area, with expected wide-ranging impact in biology, nanofabrication, and medicine. A key technical challenge lies in embedding computation in molecular contexts where electronic…

Emerging Technologies · Computer Science 2019-06-06 Marko Vasic , David Soloveichik , Sarfraz Khurshid

The mathematical formulation of Quantum Mechanics is derived from purely operational axioms based on a general definition of "experiment" as a set of transformations. The main ingredient of the mathematical construction is the postulated…

Quantum Physics · Physics 2007-05-23 Giacomo Mauro D'Ariano

Topotactic chemical reaction (TCR) is a chemical process that transforms one crystalline phase to another while maintaining one or more of the original structural frameworks, typically induced by the local insertion, removal, or replacement…

Materials Science · Physics 2024-07-03 Tappei Kawakami , Kosuke Nakayama , Katsuaki Sugawara , Takafumi Sato

Reaction networks (RNs) comprise a set $X$ of species and a set $\mathscr{R}$ of reactions $Y\to Y'$, each converting a multiset of educts $Y\subseteq X$ into a multiset $Y'\subseteq X$ of products. RNs are equivalent to directed…

Molecular Networks · Quantitative Biology 2022-01-06 Stefan Müller , Christoph Flamm , Peter F. Stadler

With the recent advances in machine learning for quantum chemistry, it is now possible to predict the chemical properties of compounds and to generate novel molecules. Existing generative models mostly use a string- or graph-based…

Biomolecules · Quantitative Biology 2020-10-14 Vitali Nesterov , Mario Wieser , Volker Roth