Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Machine intelligence for chemical reaction space
Philippe Schwaller, Alain C. Vaucher, Rubén Laplaza, et al.
Wiley Interdisciplinary Reviews Computational Molecular Science (2022) Vol. 12, Iss. 5
Open Access | Times Cited: 87

Showing 1-25 of 87 citing articles:

Augmenting large language models with chemistry tools
Andres M. Bran, Sam Cox, Oliver Schilter, et al.
Nature Machine Intelligence (2024) Vol. 6, Iss. 5, pp. 525-535
Open Access | Times Cited: 94
Scope of machine learning in materials research—A review
Md Hosne Mobarak, Mariam Akter Mimona, Md Aminul Islam, et al.
Applied Surface Science Advances (2023) Vol. 18, pp. 100523-100523
Open Access | Times Cited: 40
In Pursuit of the Exceptional: Research Directions for Machine Learning in Chemical and Materials Science
Joshua Schrier, Alexander J. Norquist, Tonio Buonassisi, et al.
Journal of the American Chemical Society (2023) Vol. 145, Iss. 40, pp. 21699-21716
Open Access | Times Cited: 39
Models Matter: the impact of single-step retrosynthesis on synthesis planning
Paula Torren-Peraire, Alan Kai Hassen, Samuel Genheden, et al.
Digital Discovery (2024) Vol. 3, Iss. 3, pp. 558-572
Open Access | Times Cited: 12
Toward a More Ethical Future of Artificial Intelligence and Data Science
Wasswa Shafik
Advances in computational intelligence and robotics book series (2024), pp. 362-388
Closed Access | Times Cited: 12
Revolutionizing the structural design and determination of covalent–organic frameworks: principles, methods, and techniques
Yikuan Liu, Xiaona Liu, An Su, et al.
Chemical Society Reviews (2023) Vol. 53, Iss. 1, pp. 502-544
Closed Access | Times Cited: 33
Molecular Machine Learning for Chemical Catalysis: Prospects and Challenges
Sukriti Singh, Raghavan B. Sunoj
Accounts of Chemical Research (2023) Vol. 56, Iss. 3, pp. 402-412
Closed Access | Times Cited: 28
AiZynthTrain: Robust, Reproducible, and Extensible Pipelines for Training Synthesis Prediction Models
Samuel Genheden, Per‐Ola Norrby, Ola Engkvist
Journal of Chemical Information and Modeling (2023) Vol. 63, Iss. 7, pp. 1841-1846
Closed Access | Times Cited: 20
Exploring Chemical Reaction Space with Machine Learning Models: Representation and Feature Perspective
Yuheng Ding, Bo Qiang, Qixuan Chen, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 8, pp. 2955-2970
Closed Access | Times Cited: 7
Artificial Intelligence for Retrosynthetic Planning Needs Both Data and Expert Knowledge
Felix Strieth‐Kalthoff, Sara Szymkuć, Karol Molga, et al.
Journal of the American Chemical Society (2024)
Closed Access | Times Cited: 7
From Characterization to Discovery: Artificial Intelligence, Machine Learning and High-Throughput Experiments for Heterogeneous Catalyst Design
Jorge Benavides-Hernández, Franck Dumeignil
ACS Catalysis (2024) Vol. 14, Iss. 15, pp. 11749-11779
Closed Access | Times Cited: 7
Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview
André Nicolle, Sili Deng, Matthias Ihme, et al.
Journal of Chemical Information and Modeling (2024) Vol. 64, Iss. 3, pp. 597-620
Closed Access | Times Cited: 6
Accelerating the Development of Sustainable Catalytic Processes through Data Science
Jason M. Stevens, Jacob M. Ganley, Matthew J. Goldfogel, et al.
Organic Process Research & Development (2025)
Closed Access
Database Construction for the Virtual Screening of the Ruthenium-Catalyzed Hydrogenation of Ketones
Hidenori Nakajima, C. Murata, Naoki Noto, et al.
The Journal of Organic Chemistry (2025) Vol. 90, Iss. 2, pp. 1054-1060
Closed Access
CLAIRE: a contrastive learning-based predictor for EC number of chemical reactions
Zishuo Zeng, Jin Guo, Jiao Jin, et al.
Journal of Cheminformatics (2025) Vol. 17, Iss. 1
Open Access
Chemical space as a unifying theme for chemistry
Jean‐Louis Reymond
Journal of Cheminformatics (2025) Vol. 17, Iss. 1
Open Access
PaRoutes: towards a framework for benchmarking retrosynthesis route predictions
Samuel Genheden, Esben Jannik Bjerrum
Digital Discovery (2022) Vol. 1, Iss. 4, pp. 527-539
Open Access | Times Cited: 27
A deep learning framework for accurate reaction prediction and its application on high-throughput experimentation data
Baiqing Li, Shimin Su, Chan Zhu, et al.
Journal of Cheminformatics (2023) Vol. 15, Iss. 1
Open Access | Times Cited: 16
Recent Applications of Machine Learning in Molecular Property and Chemical Reaction Outcome Predictions
Shilpa Shilpa, Gargee Kashyap, Raghavan B. Sunoj
The Journal of Physical Chemistry A (2023) Vol. 127, Iss. 40, pp. 8253-8271
Closed Access | Times Cited: 14
When Yield Prediction Does Not Yield Prediction: An Overview of the Current Challenges
Varvara Voinarovska, Mikhail A. Kabeshov, Dmytro Dudenko, et al.
Journal of Chemical Information and Modeling (2023) Vol. 64, Iss. 1, pp. 42-56
Closed Access | Times Cited: 14
Prediction of chemical reaction yields with large-scale multi-view pre-training
Runhan Shi, Gufeng Yu, Xiaohong Huo, et al.
Journal of Cheminformatics (2024) Vol. 16, Iss. 1
Open Access | Times Cited: 5
Retro-BLEU: quantifying chemical plausibility of retrosynthesis routes through reaction template sequence analysis
Junren Li, Lei Fang, Jian–Guang Lou
Digital Discovery (2024) Vol. 3, Iss. 3, pp. 482-490
Open Access | Times Cited: 4
Top 20 influential AI-based technologies in chemistry
Valentine P. Ananikov
Artificial Intelligence Chemistry (2024) Vol. 2, Iss. 2, pp. 100075-100075
Open Access | Times Cited: 4
Transformers and Large Language Models for Chemistry and Drug Discovery
Andres M. Bran, Philippe Schwaller
(2024), pp. 143-163
Closed Access | Times Cited: 4
Bridging Chemical Knowledge and Machine Learning for Performance Prediction of Organic Synthesis
Shuo‐Qing Zhang, Li‐Cheng Xu, Shu‐Wen Li, et al.
Chemistry - A European Journal (2022) Vol. 29, Iss. 6
Open Access | Times Cited: 25
Page 1 - Next Page

Scroll to top