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Probability Guided Chemical Reaction Scopes

https://doi.org/10.2139/ssrn.5138219
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Parallel Optimization of Synthetic Pathways within the Network of Organic Chemistry
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Rate and Equilibrium Constants for the Addition of N‐Heterocyclic Carbenes into Benzaldehydes: A Remarkable 2‐Substituent Effect
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Small Data Can Play a Big Role in Chemical Discovery
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Small data in the era of big data
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Computer-assisted organic synthesis design and reaction prediction system, “AIPHOS”
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Effects of dataset size and interactions on the prediction performance of logistic regression and deep learning models
inferredcites →https://doi.org/10.1016/j.drudis.2018.02.014openalex-snapshot
Computational prediction of chemical reactions: current status and outlook
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When small data beats big data
inferredcites →https://doi.org/10.1016/j.xcrp.2020.100247openalex-snapshot
Adaptive Optimization of Chemical Reactions with Minimal Experimental Information
inferredcites →https://doi.org/10.1016/s0003-2670(00)82062-0openalex-snapshot
Computer-assisted reaction prediction and synthesis design
inferredcites →https://doi.org/10.1021/acs.chemrev.2c00798openalex-snapshot
A Brief Introduction to Chemical Reaction Optimization
inferredcites →https://doi.org/10.1021/acs.chemrev.3c00189openalex-snapshot
Machine Learning Methods for Small Data Challenges in Molecular Science
inferredcites →https://doi.org/10.1021/acs.chemrev.8b00507openalex-snapshot
3d Transition Metals for C–H Activation
inferredcites →https://doi.org/10.1021/acs.jcim.0c01234openalex-snapshot
Multilabel Classification Models for the Prediction of Cross-Coupling Reaction Conditions
inferredcites →https://doi.org/10.1021/acs.jcim.1c00284openalex-snapshot
Automated Chemical Reaction Extraction from Scientific Literature
inferredcites →https://doi.org/10.1021/acs.jcim.9b00313openalex-snapshot
Learning To Predict Reaction Conditions: Relationships between Solvent, Molecular Structure, and Catalyst
inferredcites →https://doi.org/10.1021/acs.orglett.2c03246openalex-snapshot
On the Topic of Substrate Scope
inferredcites →https://doi.org/10.1021/acscatal.1c04583openalex-snapshot
Rerouting the Organocatalytic Benzoin Reaction toward Aldehyde Deuteration
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Mechanistic Inference from Statistical Models at Different Data-Size Regimes
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Bayesian Optimization of Computer-Proposed Multistep Synthetic Routes on an Automated Robotic Flow Platform
inferredcites →https://doi.org/10.1021/acscentsci.3c01638openalex-snapshot
Standardizing Substrate Selection: A Strategy toward Unbiased Evaluation of Reaction Generality
inferredcites →https://doi.org/10.1021/acscentsci.6b00219openalex-snapshot
Neural Networks for the Prediction of Organic Chemistry Reactions
inferredcites →https://doi.org/10.1021/acscentsci.7b00303openalex-snapshot
Retrosynthetic Reaction Prediction Using Neural Sequence-to-Sequence Models
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Optimizing Chemical Reactions with Deep Reinforcement Learning
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Phoenics: A Bayesian Optimizer for Chemistry
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Using Machine Learning To Predict Suitable Conditions for Organic Reactions
inferredcites →https://doi.org/10.1021/acscentsci.9b00576openalex-snapshot
Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction
inferredcites →https://doi.org/10.1021/ja308420copenalex-snapshot
Proton Transfer Reactions of Triazol-3-ylidenes: Kinetic Acidities and Carbon Acid p K a Values for Twenty Triazolium Salts in Aqueous Solution
inferredcites →https://doi.org/10.1021/jacs.0c04674openalex-snapshot
Selective Halogenation of Pyridines Using Designed Phosphine Reagents
inferredcites →https://doi.org/10.1021/jacs.2c08513openalex-snapshot
Data-Driven Multi-Objective Optimization Tactics for Catalytic Asymmetric Reactions Using Bisphosphine Ligands
inferredcites →https://doi.org/10.1021/jacs.8b01523openalex-snapshot
Deoxyfluorination with Sulfonyl Fluorides: Navigating Reaction Space with Machine Learning
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ROBIA: A Reaction Prediction Program
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Planning chemical syntheses with deep neural networks and symbolic AI
inferredcites →https://doi.org/10.1038/nrd.2018.116openalex-snapshot
Expanding the medicinal chemistry synthetic toolbox
inferredcites →https://doi.org/10.1038/s41557-019-0258-1openalex-snapshot
Unravelling mechanistic features of organocatalysis with in situ modifications at the secondary sphere
inferredcites →https://doi.org/10.1038/s41586-018-0337-2openalex-snapshot
Machine learning for molecular and materials science
inferredcites →https://doi.org/10.1038/s41586-021-03213-yopenalex-snapshot
Bayesian reaction optimization as a tool for chemical synthesis
inferredcites →https://doi.org/10.1038/s41586-022-05263-2openalex-snapshot
Screening for generality in asymmetric catalysis
inferredcites →https://doi.org/10.1038/s41586-024-07021-yopenalex-snapshot
Identifying general reaction conditions by bandit optimization
inferredcites →https://doi.org/10.1038/s42004-021-00550-xopenalex-snapshot
Data-science driven autonomous process optimization
inferredcites →https://doi.org/10.1038/s44160-023-00271-0openalex-snapshot
A neural network model informs the total synthesis of clovane sesquiterpenoids
inferredcites →https://doi.org/10.1038/s44160-023-00297-4openalex-snapshot
Predicting synthetic viability
inferredcites →https://doi.org/10.1039/c2sc22137copenalex-snapshot
Mechanistic insights into the triazolylidene-catalysed Stetter and benzoin reactions: role of the N-aryl substituent
inferredcites →https://doi.org/10.1039/c8sc02239aopenalex-snapshot
Chimera: enabling hierarchy based multi-objective optimization for self-driving laboratories
inferredcites →https://doi.org/10.1039/c9cs00786eopenalex-snapshot
Machine learning the ropes: principles, applications and directions in synthetic chemistry
inferredcites →https://doi.org/10.1039/c9ob01994dopenalex-snapshot
Recent advances in cobalt-catalysed C–H functionalizations
inferredcites →https://doi.org/10.1039/d1cc04382jopenalex-snapshot
C–H bond functionalization by high-valent cobalt catalysis: current progress, challenges and future perspectives
inferredcites →https://doi.org/10.1039/d1sc06932bopenalex-snapshot
Predicting reaction conditions from limited data through active transfer learning
inferredcites →https://doi.org/10.1088/2632-2153/abc81dopenalex-snapshot
Prediction of chemical reaction yields using deep learning
inferredcites →https://doi.org/10.1126/science.1259203openalex-snapshot
Nanomole-scale high-throughput chemistry for the synthesis of complex molecules
inferredcites →https://doi.org/10.1126/science.aaf3539openalex-snapshot
The straight dope on the scope of chemical reactions
inferredcites →https://doi.org/10.1126/science.abn1885openalex-snapshot
Accelerating reaction generality and mechanistic insight through additive mapping
inferredcites →https://doi.org/10.1126/science.adc8743openalex-snapshot
Closed-loop optimization of general reaction conditions for heteroaryl Suzuki-Miyaura coupling
inferredcites →https://doi.org/10.1126/science.adg2114openalex-snapshot
A machine-learning tool to predict substrate-adaptive conditions for Pd-catalyzed C–N couplings
inferredcites →https://doi.org/10.26434/chemrxiv-2023-bmg14openalex-snapshot
Cp*Co-catalyzed directed hydrogen isotope exchange with substrate-dependent deuterium source

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1021/jacs.6c00127openalex-snapshot
Yield Prediction of Organic Reactions in Biased Data Sets via Positive-Unlabeled Learning
inferred← citeshttps://doi.org/10.1039/d5sc03045eopenalex-snapshot
Predicting reaction conditions: a data-driven perspective
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