BetaCitation Atlas

RESEARCH PAPER · Cell Reports Physical Science · 2020

Adaptive Optimization of Chemical Reactions with Minimal Experimental Information

Daniel Reker, Emily A. Hoyt, Gonçalo J. L. Bernardes, Tiago Rodrigues

Read original paper ↗

See where this research leads.

82 direct citing papers in this saved network. Explore the next layer with second-order citations.

Open in your workspace →Saved 2026-10-14 · complete coverage
Filter Citing Papers
Press Enter or comma to add · × to remove · searches titles and available abstracts
Journals
All journals
Most represented first · select one or more
Explore Terms In These PapersHide SuggestionsShow Suggestions

Original and current center papers stay visible as anchors.
Numbers show citations received
42 direct citing works

Adaptive Optimization of Chemical Reactions with Minimal Experimental InformationOriginalA Toolbox for the Identification of Modes of Action of Natural Products2Deep Learning in Chemistry561Synthetic organic chemistry driven by artificial intelligence303Autonomous Discovery in the Chemical Sciences Part I: Progress317Machine learning for target discovery in drug development61Practical considerations for active machine learning in drug discovery95The good, the bad, and the ugly in chemical and biological data for machine learning53Molecular Machine Learning: The Future of Synthetic Chemistry?72Bayesian reaction optimization as a tool for chemical synthesis1044Machine learning made easy for optimizing chemical reactions21Automation and computer-assisted planning for chemical synthesis189Augmenting Adaptive Machine Learning with Kinetic Modeling for Reaction Optimization20Autonomous experimentation systems for materials development: A community perspective398Prediction of Multicomponent Reaction Yields Using Machine Learning33Application of an Electrochemical Microflow Reactor for Cyanosilylation: Machine Learning-Assisted Exploration of Suitable Reaction Conditions for Semi-Large-Scale Synthesis36Chemputation and the Standardization of Chemical Informatics73Combating small-molecule aggregation with machine learning21New trends in nonconventional carbon dot synthesis60Transition to sustainable chemistry through digitalization85Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases37Deriving intuition in catalyst design with machine learning5Chemically-informed data-driven optimization (ChIDDO): leveraging physical models and Bayesian learning to accelerate chemical research21Hyperconverged autonomous organic reaction infrastructure (HAORI) driven by SpecSNN, for low dielectric constant polymer research2Nuisance small molecules under a machine-learning lens3Predicting reaction conditions from limited data through active transfer learning78Evaluation guidelines for machine learning tools in the chemical sciences180A special issue on artificial intelligence for drug discovery0Machine Learning Modeling of Environmentally Relevant Chemical Reactions for Organic Compounds33The Automated Synthesis of Aspirin: An Undergraduate Practical Activity9Machine Learning Yield Prediction from NiCOlit, a Small-Size Literature Data Set of Nickel Catalyzed C–O Couplings87Bayesian optimization of electrochemical devices for electrons-to-molecules conversions: the case of pulsed CO 2 electroreduction17Closed-loop optimization of general reaction conditions for heteroaryl Suzuki-Miyaura coupling208Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery138ACCELERATING DRUG DISCOVERY BY HIGH-THROUGHPUT EXPERIMENTATION1Diversifying Design of Nucleic Acid Aptamers Using Unsupervised Machine Learning10A field guide to flow chemistry for synthetic organic chemists393A focus on the use of real-world datasets for yield prediction3Modeling and Optimization of Hydrogen Production from Methanol-Steam Reforming Using Response Surface Methodology and Artificial Neural Network1The rise of automated curiosity-driven discoveries in chemistry20Navigating with chemometrics and machine learning in chemistry56Small Data Can Play a Big Role in Chemical Discovery38Small Data Can Play a Big Role in Chemical Discovery7Prediction of thermal diffusivity of volcanic rocks using machine learning and genetic algorithm hybrid strategy8Machine Learning Strategies for Reaction Development: Toward the Low-Data Limit39Bayesian-optimization-assisted discovery of stereoselective aluminum complexes for ring-opening polymerization of racemic lactide68Rapid planning and analysis of high-throughput experiment arrays for reaction discovery83Machine Learning for the Optimization of Chemical Reaction Conditions6Limitations of representation learning in small molecule property prediction17Yoked learning in molecular data science4When Yield Prediction Does Not Yield Prediction: An Overview of the Current Challenges64Advanced machine learning for automated chemical reaction balancing: A systematic review0Digital chemistry: navigating the confluence of computation and experimentation – definition, status quo, and future perspective11Helping chemists help themselves0Automated Experimentation Enables a Data-Driven Model for Palladium Removal with Aqueous Chelators1Identifying general reaction conditions by bandit optimization72The landscape of small-molecule prodrugs150CIME4R: Exploring iterative, AI-guided chemical reaction optimization campaigns in their parameter space4Virtual Variables as Powerful and Reliable Parameters to Predict Experimentally Unobservable Reactions in Organic Synthesis1Utopia Point Bayesian Optimization Finds Condition-Dependent Selectivity for N-Methyl Pyrazole Condensation25Data-driven learning of structure augments quantitative prediction of biological responses1Benchmarking Strategies of Sustainable Process Chemistry Development: Human-Based, Machine Learning, and Quantum Mechanics9Computer‐Aided Synthesis Planning (CASP) and Machine Learning: Optimizing Chemical Reaction Conditions15Powerful and Reliable Prediction using Latent Variables of Experimentally Unobservable Reactions in Organic Synthesis1Powerful and Reliable Prediction using Latent Variables of Experimentally Unobservable Reactions in Organic Synthesis1Finding the most potent compounds using active learning on molecular pairs9Catalysing (organo-)catalysis: Trends in the application of machine learning to enantioselective organocatalysis17Hydrogen production optimization from methanol steam reforming using Box-Behnken design, analysis of variance, and artificial neural network12MPCD: A Multitask Graph Transformer for Molecular Property Prediction by Integrating Common and Domain Knowledge17Active learning assists chemical intuition identify a scalable conversion of chitin to 3-acetamido-5-acetylfuran7Linking mechanics and chemistry: machine learning for yield prediction in NaBH 4 mechanochemical regeneration5Machine Learning Applications in Drug Discovery5Optimising Materials Properties with Minimal Data: Lessons from Vanadium Catalyst Modelling1Probability Guided Chemical Reaction Scopes232nd Annual GP2A Medicinal Chemistry Conference0An active representation learning method for reaction yield prediction with small-scale data8The Implementation and Impact of Chemical High-Throughput Experimentation at AstraZeneca36The Potential of Generative AI in Drug Development0Towards greener-by-design fine chemicals. Part 2: technological frontiers12MIK-I: a portable low-cost platform for automated C–C bond synthesis0Machine Learning and Autonomous Systems for Accelerated Synthesis1Machine Learning for Synthetic Organic Chemistry: Methods, Applications, and Best Practices0Integration of Liquid Handling Robotics, Turbidimetry, and Machine Learning Toward Inverse Design of Lower Critical Solution Temperature Polymer Formulations0

Arrows point to the paper being cited. Selecting a paper shows its incoming citations and its known path back to the original paper.

Drag to pan · Use + / − to zoom · Escape to close43 nodes / 53 citation links
Browse Matching Papers

Papers that cite this work

82 direct citing papers saved. Showing the first 50 here; use Browse Matching Papers in the map for all loaded papers.

  1. A Toolbox for the Identification of Modes of Action of Natural Products

    Fortschritte der Chemie Organischer Naturstoffe/Fortschritte der Chemie organischer Naturstoffe/Progress in the chemistry of organic natural products · 2019-01-01

    Tiago Rodrigues

    Read original paper ↗ ·

  2. Deep Learning in Chemistry

    Journal of Chemical Information and Modeling · 2019-06-13

    Adam C. Mater, Michelle L. Coote

    Read original paper ↗ ·

  3. Synthetic organic chemistry driven by artificial intelligence

    Nature Reviews Chemistry · 2019-08-21

    A. Filipa Almeida, Rui Moreira, Tiago Rodrigues

    Read original paper ↗ ·

  4. Autonomous Discovery in the Chemical Sciences Part I: Progress

    Angewandte Chemie International Edition · 2019-09-25

    Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen

    Read original paper ↗ ·

  5. Machine learning for target discovery in drug development

    Current Opinion in Chemical Biology · 2019-11-14

    Tiago Rodrigues, Gonçalo J. L. Bernardes

    Read original paper ↗ ·

  6. Practical considerations for active machine learning in drug discovery

    Drug Discovery Today Technologies · 2019-12-01

    Daniel Reker

    Read original paper ↗ ·

  7. The good, the bad, and the ugly in chemical and biological data for machine learning

    Drug Discovery Today Technologies · 2019-12-01

    Tiago Rodrigues

    Read original paper ↗ ·

  8. Molecular Machine Learning: The Future of Synthetic Chemistry?

    Angewandte Chemie International Edition · 2020-09-15

    Philipp Miro Pflüger, Frank Glorius

    Read original paper ↗ ·

  9. Bayesian reaction optimization as a tool for chemical synthesis

    Nature · 2021-02-03

    Benjamin J. Shields, Jason M. Stevens, Jun Li, Marvin Parasram, Farhan Damani, Jesus I. Martinez Alvarado, Jacob M. Janey, Ryan Prescott Adams, Abigail G. Doyle

    Read original paper ↗ ·

  10. Machine learning made easy for optimizing chemical reactions

    Nature · 2021-02-03

    Jason E. Hein

    Read original paper ↗ ·

  11. Automation and computer-assisted planning for chemical synthesis

    Nature Reviews Methods Primers · 2021-03-18

    Yuning Shen, Julia E. Borowski, Melissa A. Hardy, Richmond Sarpong, Abigail G. Doyle, Tim Cernak

    Read original paper ↗ ·

  12. Augmenting Adaptive Machine Learning with Kinetic Modeling for Reaction Optimization

    The Journal of Organic Chemistry · 2021-07-08

    A. Filipa Almeida, Filipe Ataíde, Rui M. S. Loureiro, Rui Moreira, Tiago Rodrigues

    Read original paper ↗ ·

  13. Autonomous experimentation systems for materials development: A community perspective

    Matter · 2021-07-26

    Eric A. Stach, Brian DeCost, Aaron Gilad Kusne, Jason R. Hattrick-Simpers, Keith A. Brown, Kristofer G. Reyes, Joshua Schrier, Simon J. L. Billinge, Tonio Buonassisi, Ian T Foster, Carla Pedro Gomes, John M. Gregoire, Apurva Mehta, Joseph H. Montoya, Elsa Olivetti, Chiwoo Park, Eli Rotenberg, Semion K. Saikin, Sylvia Smullin, Valentin Stanev, Benji Maruyama

    Read original paper ↗ ·

  14. Prediction of Multicomponent Reaction Yields Using Machine Learning

    Chinese Journal of Chemistry · 2021-08-04

    Xingyong Zhu, Chuan‐Kun Ran, Ming Fen Wen, Gui‐Ling Guo, Yuan Liu, Li‐Li Liao, Yi‐Zhou Li, Meng‐Long Li, Da‐Gang Yu

    Read original paper ↗ ·

  15. Application of an Electrochemical Microflow Reactor for Cyanosilylation: Machine Learning-Assisted Exploration of Suitable Reaction Conditions for Semi-Large-Scale Synthesis

    The Journal of Organic Chemistry · 2021-08-06

    Eisuke F. Sato, Mayu Fujii, Hiroki Tanaka, Koichi Mitsudo, Masaru Kondo, Shinobu Takizawa, Hiroaki Sasai, Takeshi Washio, Kazunori Ishikawa, Seiji Suga

    Read original paper ↗ ·

  16. Chemputation and the Standardization of Chemical Informatics

    JACS Au · 2021-08-31

    Alexander J. S. Hammer, Artem I. Leonov, Nicola L. Bell, Leroy Cronin

    Read original paper ↗ ·

  17. Combating small-molecule aggregation with machine learning

    Cell Reports Physical Science · 2021-09-01

    Kuan Lee, Ann Yang, Yen‐Chu Lin, Daniel Reker, Gonçalo J. L. Bernardes, Tiago Rodrigues

    Read original paper ↗ ·

  18. New trends in nonconventional carbon dot synthesis

    Trends in Chemistry · 2021-10-01

    Beatrice Bartolomei, Jacopo Dosso, Maurizio Prato

    Read original paper ↗ ·

  19. Transition to sustainable chemistry through digitalization

    Chem · 2021-10-22

    Peter Fantke, Claudio Cinquemani, Polina Yaseneva, Jonathas De Mello, Henning Schwabe, Bjoern Ebeling, Alexei A. Lapkin

    Read original paper ↗ ·

  20. Artificial Intelligence, Machine Learning, and Deep Learning in Real-Life Drug Design Cases

    Methods in molecular biology · 2021-11-03

    Christophe Müller, Obdulia Rabal, Constantino Diaz Gonzalez

    Read original paper ↗ ·

  21. Deriving intuition in catalyst design with machine learning

    Chem · 2021-12-30

    Tiago Rodrigues

    Read original paper ↗ ·

  22. Chemically-informed data-driven optimization (ChIDDO): leveraging physical models and Bayesian learning to accelerate chemical research

    Reaction Chemistry & Engineering · 2022-01-01

    Daniel Frey, Ju Hee Shin, Christopher Musco, Miguel Antonio Modestino

    Read original paper ↗ ·

  23. Hyperconverged autonomous organic reaction infrastructure (HAORI) driven by SpecSNN, for low dielectric constant polymer research

    Digital Discovery · 2022-01-01

    Yanheng Xu, Kai-Bin Qiu, Shuyu Xiao, Jiechun Liang, Tingchao He, Xi Zhu

    Read original paper ↗ ·

  24. Nuisance small molecules under a machine-learning lens

    Digital Discovery · 2022-01-01

    Tiago Rodrigues

    Read original paper ↗ ·

  25. Predicting reaction conditions from limited data through active transfer learning

    Chemical Science · 2022-01-01

    Eunjae Shim, Joshua A. Kammeraad, Ziping Xu, Ambuj Tewari, Tim Cernak, Paul M. Zimmerman

    Read original paper ↗ ·

  26. Evaluation guidelines for machine learning tools in the chemical sciences

    Nature Reviews Chemistry · 2022-05-24

    Andreas Bender, Nadine Schneider, Marwin Segler, W. Patrick Walters, Ola Engkvist, Tiago Rodrigues

    Read original paper ↗ ·

  27. A special issue on artificial intelligence for drug discovery

    Bioorganic & Medicinal Chemistry · 2022-07-14

    Tiago Rodrigues

    Read original paper ↗ ·

  28. Machine Learning Modeling of Environmentally Relevant Chemical Reactions for Organic Compounds

    ACS ES&T Water · 2022-07-19

    Kai Zhang, Huichun Judy Zhang

    Read original paper ↗ ·

  29. The Automated Synthesis of Aspirin: An Undergraduate Practical Activity

    Journal of Chemical Education · 2022-07-28

    Matthew Nel, Kariska Potgieter, Oyekunle Azeez Alimi, André Nel, Reinout Meijboom

    Read original paper ↗ ·

  30. Machine Learning Yield Prediction from NiCOlit, a Small-Size Literature Data Set of Nickel Catalyzed C–O Couplings

    Journal of the American Chemical Society · 2022-08-08

    Jules Schleinitz, Maxime Langevin, Yanis Smail, Benjamin Wehnert, Laurence Grimaud, Rodolphe Vuilleumier

    Read original paper ↗ ·

  31. Bayesian optimization of electrochemical devices for electrons-to-molecules conversions: the case of pulsed CO 2 electroreduction

    Reaction Chemistry & Engineering · 2022-10-21

    Daniel Frey, Kenneth Charles Neyerlin, Miguel Antonio Modestino

    Read original paper ↗ ·

  32. Closed-loop optimization of general reaction conditions for heteroaryl Suzuki-Miyaura coupling

    Science · 2022-10-27

    Nicholas H. Angello, Vandana Rathore, Wiktor Beker, Agnieszka Wołos, Edward R. Jira, Rafał Roszak, Tony Wu, Charles M. Schroeder, Alán Aspuru‐Guzik, Bartosz A. Grzybowski, Martin D. Burke

    Read original paper ↗ ·

  33. Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery

    Chemical Science · 2022-11-28

    Zhengkai Tu, Thijs Stuyver, Connor W. Coley

    Read original paper ↗ ·

  34. ACCELERATING DRUG DISCOVERY BY HIGH-THROUGHPUT EXPERIMENTATION

    Medicinal chemistry reviews · 2022-12-21

    Jose R. Montero Bastidas, Abdellatif El Marrouni, Maria Irina Chiriac, Thomas J. Struble, Dipannita Kalyani

    Read original paper ↗ ·

  35. Diversifying Design of Nucleic Acid Aptamers Using Unsupervised Machine Learning

    The Journal of Physical Chemistry B · 2022-12-27

    Siba Moussa, Michael Kilgour, Clara Jans, Álex Hernández-García, Miroslava Čuperlović‐Culf, Yoshua Bengio, Lena Simine

    Read original paper ↗ ·

  36. A field guide to flow chemistry for synthetic organic chemists

    Chemical Science · 2023-01-01

    Luca Capaldo, Zhenghui Wen, Timothy Noël

    Read original paper ↗ ·

  37. A focus on the use of real-world datasets for yield prediction

    Chemical Science · 2023-01-01

    Latimah Bustillo, Tiago Rodrigues

    Read original paper ↗ ·

  38. Modeling and Optimization of Hydrogen Production from Methanol-Steam Reforming Using Response Surface Methodology and Artificial Neural Network

    SSRN Electronic Journal · 2023-01-01

    Wei‐Hsin Chen, Chun-Yin Cheng, Yi-Kai Chih, Reiyu Chein, Young‐Kwon Park, Amit Kumar Sharma

    Read original paper ↗ ·

  39. The rise of automated curiosity-driven discoveries in chemistry

    Chemical Science · 2023-01-01

    Latimah Bustillo, Teodoro Laino, Tiago Rodrigues

    Read original paper ↗ ·

  40. Navigating with chemometrics and machine learning in chemistry

    Artificial Intelligence Review · 2023-01-23

    Payal B. Joshi

    Read original paper ↗ ·

  41. Small Data Can Play a Big Role in Chemical Discovery

    Angewandte Chemie International Edition · 2023-03-23

    Hadas Shalit Peleg, Anat Milo

    Read original paper ↗ ·

  42. Small Data Can Play a Big Role in Chemical Discovery

    Angewandte Chemie · 2023-03-23

    Hadas Shalit Peleg, Anat Milo

    Read original paper ↗ ·

  43. Prediction of thermal diffusivity of volcanic rocks using machine learning and genetic algorithm hybrid strategy

    International Journal of Thermal Sciences · 2023-05-16

    Muhammad Nouman Aslam Khan, Usman Ghafoor, Abdullah Abdullah, Zeeshan Ul Haq, Hafeez Ullah, Iftikhar Hussain Gul, Asghari Maqsood

    Read original paper ↗ ·

  44. Machine Learning Strategies for Reaction Development: Toward the Low-Data Limit

    Journal of Chemical Information and Modeling · 2023-06-14

    Eunjae Shim, Ambuj Tewari, Tim Cernak, Paul M. Zimmerman

    Read original paper ↗ ·

  45. Bayesian-optimization-assisted discovery of stereoselective aluminum complexes for ring-opening polymerization of racemic lactide

    Nature Communications · 2023-06-20

    Xiaoqian Wang, Yang Huang, Xiaoyu Xie, Yan Liu, Ziyu Huo, Maverick Lin, Hongliang Xin, Rong Tong

    Read original paper ↗ ·

  46. Rapid planning and analysis of high-throughput experiment arrays for reaction discovery

    Nature Communications · 2023-07-03

    Babak A. Mahjour, Rui Zhang, Yuning Shen, Andrew McGrath, Ruheng Zhao, Osama G. Mohamed, Yingfu Lin, Zirong Zhang, James L. Douthwaite, Ashootosh Tripathi, Tim Cernak

    Read original paper ↗ ·

  47. Machine Learning for the Optimization of Chemical Reaction Conditions

    Unknown journal · 2023-08-31

    A. Filipa Almeida, Tiago Rodrigues

    Read original paper ↗ ·

  48. Limitations of representation learning in small molecule property prediction

    Nature Communications · 2023-10-13

    Ana Laura Dias, Latimah Bustillo, Tiago Rodrigues

    Read original paper ↗ ·

  49. Yoked learning in molecular data science

    Artificial Intelligence in the Life Sciences · 2023-12-02

    Zhixiong Li, Yan Xiang, Yujing Wen, Daniel Reker

    Read original paper ↗ ·

  50. When Yield Prediction Does Not Yield Prediction: An Overview of the Current Challenges

    Journal of Chemical Information and Modeling · 2023-12-20

    Varvara Voinarovska, Mikhail Kabeshov, Dmytro Dudenko, Samuel Genheden, Igor V. Tetko

    Read original paper ↗ ·
More citing papers →
Citation Atlas · A map of research, not a ranking.