ReviewThe journal of physical chemistry. A2022
Graph-Driven Reaction Discovery: Progress, Challenges, and Future Opportunities.
Review in The journal of physical chemistry. A, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
19 citing papers in PubMed.
- Graph-Based Generation and Reduction of Complex Chemical Reaction Networks.Journal of chemical information and modeling · 2026Article
- Automated Discovery of Algorithms for Molecular Electronic Structure Calculations Using Physics-Informed Program Synthesis.Journal of the American Chemical Society · 2026Article
- How Does Adenine Form from Hydrogen Cyanide?Journal of the American Chemical Society · 2026Article
- The seeds of the future are in the present: A blind exploration of metastable states.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Lifelong Machine Learning Potentials for Chemical Reaction Network Explorations.Journal of chemical theory and computation · 2025Article
- Harnessing Machine Learning to Enhance Transition State Search with Interatomic Potentials and Generative Models.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Automated Microsolvation for Minimum Energy Path Construction in Solution.Journal of chemical theory and computation · 2025Article
- Machine learning and data-driven methods in computational surface and interface science.npj computational materials · 2025Review
- Heron: Visualizing and Controlling Chemical Reaction Explorations and Networks.The journal of physical chemistry. A · 2024Article
- Reactant Discovery with anACS earth & space chemistry · 2024Article
- Contact-Map-Driven Exploration of Heterogeneous Protein-Folding Paths.Journal of chemical theory and computation · 2024Article
- Predicting Long-Time-Scale Kinetics under Variable Experimental Conditions with Kinetica.jl.Journal of chemical theory and computation · 2024Article
- Nanoscale chemical reaction exploration with a quantum magnifying glass.Nature communications · 2024Article
- A human-machine interface for automatic exploration of chemical reaction networks.Nature communications · 2024Article
- Exploring Chemical Space UsingACS central science · 2024Article
- Diffusion-based generative AI for exploring transition states from 2D molecular graphs.Nature communications · 2024Article
- Navigating the Expansive Landscapes of Soft Materials: A User Guide for High-Throughput Workflows.ACS polymers Au · 2023Review
- ΔChemical science · 2023Article
- Generating Protein Folding Trajectories Using Contact-Map-Driven Directed Walks.Journal of chemical information and modeling · 2023Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Graph-based descriptors, such as bond-order matrices and adjacency matrices, offer a simple and compact way of categorizing molecular structures; furthermore, such descriptors can be readily used to catalog chemical reactions (i.e., bond-making and -breaking). As such, a number of graph-based methodologies have been developed with the goal of automating the process of generating chemical reaction network models describing the possible mechanistic chemistry in a given set of reactant species. Here, we outline the evolution of these graph-based reaction discovery schemes, with particular emphasis on more recent methods incorporating graph-based methods with semiempirical and
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Registered trials
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