相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。Machine-Learning-Guided Discovery of Electrochemical Reactions
Andrew F. Zahrt et al.
JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2022)
Convergence of multiple synthetic paradigms in a universally programmable chemical synthesis machine
Davide Angelone et al.
NATURE CHEMISTRY (2021)
Discovery of novel chemical reactions by deep generative recurrent neural network
William Bort et al.
SCIENTIFIC REPORTS (2021)
Discovering New Chemistry with an Autonomous Robotic Platform Driven by a Reactivity-Seeking Neural Network
Dario Caramelli et al.
ACS CENTRAL SCIENCE (2021)
Bias free multiobjective active learning for materials design and discovery
Kevin Maik Jablonka et al.
NATURE COMMUNICATIONS (2021)
On Interpretability of Artificial Neural Networks: A Survey
Feng-Lei Fan et al.
IEEE TRANSACTIONS ON RADIATION AND PLASMA MEDICAL SCIENCES (2021)
Organic reactivity from mechanism to machine learning
Kjell Jorner et al.
NATURE REVIEWS CHEMISTRY (2021)
Navigating through the Maze of Homogeneous Catalyst Design with Machine Learning
Gabriel dos Passos Gomes et al.
TRENDS IN CHEMISTRY (2021)
Autonomous Discovery in the Chemical Sciences Part I: Progress
Connor W. Coley et al.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2020)
Self-driving laboratory for accelerated discovery of thin-film materials
B. P. MacLeod et al.
SCIENCE ADVANCES (2020)
A universal system for digitization and automatic execution of the chemical synthesis literature
S. Hessam M. Mehr et al.
SCIENCE (2020)
Organic synthesis in a modular robotic system driven by a chemical programming language
Sebastian Steiner et al.
SCIENCE (2019)
Advances and challenges in deep generative models for de novo molecule generation
Dongyu Xue et al.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE (2019)
Accelerated robotic discovery of type II porous liquids
Rachel J. Kearsey et al.
CHEMICAL SCIENCE (2019)
Machine Learning for Organic Synthesis: Are Robots Replacing Chemists?
Boris Maryasin et al.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION (2018)
Controlling an organic synthesis robot with machine learning to search for new reactivity
Jaroslaw M. Granda et al.
NATURE (2018)
Machine learning for molecular and materials science
Keith T. Butler et al.
NATURE (2018)
An efficient palladium catalyzed Mizoroki-Heck cross-coupling in water
Sanjay N. Jadhav et al.
GREEN CHEMISTRY (2017)
Stan: A Probabilistic Programming Language
Bob Carpenter et al.
JOURNAL OF STATISTICAL SOFTWARE (2017)
An autonomous organic reaction search engine for chemical reactivity
Vincenza Dragone et al.
NATURE COMMUNICATIONS (2017)
Prediction of Organic Reaction Outcomes Using Machine Learning
Connor W. Coley et al.
ACS CENTRAL SCIENCE (2017)
A critical review of high entropy alloys and related concepts
D. B. Miracle et al.
ACTA MATERIALIA (2017)
Modelling Chemical Reasoning to Predict and Invent Reactions
Marwin H. S. Segler et al.
CHEMISTRY-A EUROPEAN JOURNAL (2017)
Neural-Symbolic Machine Learning for Retrosynthesis and Reaction Prediction
Marwin H. S. Segler et al.
CHEMISTRY-A EUROPEAN JOURNAL (2017)
Probabilistic programming in Python using PyMC3
John Salvatier et al.
PEERJ COMPUTER SCIENCE (2016)
Molecular fingerprint similarity search in virtual screening
Adria Cereto-Massague et al.
METHODS (2015)
Dark chemical matter as a promising starting point for drug lead discovery
Anne Mai Wassermann et al.
NATURE CHEMICAL BIOLOGY (2015)
Nanomole-scale high-throughput chemistry for the synthesis of complex molecules
Alexander Buitrago Santanilla et al.
SCIENCE (2015)
P7C3 and an unbiased approach to drug discovery for neurodegenerative diseases
Andrew A. Pieper et al.
CHEMICAL SOCIETY REVIEWS (2014)
Atom Pair 2D-Fingerprints Perceive 3D-Molecular Shape and Pharmacophores for Very Fast Virtual Screening of ZINC and GDB-17
Mahendra Awale et al.
JOURNAL OF CHEMICAL INFORMATION AND MODELING (2014)
Contemporary screening approaches to reaction discovery and development
Karl D. Collins et al.
NATURE CHEMISTRY (2014)
Philosophy and the practice of Bayesian statistics
Andrew Gelman et al.
BRITISH JOURNAL OF MATHEMATICAL & STATISTICAL PSYCHOLOGY (2013)
Estimation of the size of drug-like chemical space based on GDB-17 data
P. G. Polishchuk et al.
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN (2013)
Inside the Mind of a Medicinal Chemist: The Role of Human Bias in Compound Prioritization during Drug Discovery
Peter S. Kutchukian et al.
PLOS ONE (2012)
Synthesis of aryl alkynyl carboxylic acids and aryl allrynes from propiolic acid and aryl halides by site selective coupling and decarboxylation
Kyungho Park et al.
TETRAHEDRON LETTERS (2012)
The enumeration of chemical space
Jean-Louis Reymond et al.
WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE (2012)
Discovery of an α-Amino C-H Arylation Reaction Using the Strategy of Accelerated Serendipity
Andrew McNally et al.
SCIENCE (2011)
Solvent-free Horner-Wadsworth-Emmons reaction using DBU
Kaori Ando et al.
TETRAHEDRON LETTERS (2010)
SnCl2-catalyzed three-component one-pot Mannich-type reaction: efficient synthesis of β-aminocarbonyl compounds
Min Wang et al.
MONATSHEFTE FUR CHEMIE (2009)
Effects of inductive bias on computational evaluations of ligand-based modeling and on drug discovery
Ann E. Cleves et al.
JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN (2008)
Commercializing generic technology: The case of advanced materials ventures
E Maine et al.
RESEARCH POLICY (2006)
Expedited palladium-catalyzed amination of aryl nonaflates through the use of microwave-irradiation and soluble organic amine bases
RE Tundel et al.
JOURNAL OF ORGANIC CHEMISTRY (2006)
Wittig reaction by using DBU as a base
K Okuma et al.
BULLETIN OF THE CHEMICAL SOCIETY OF JAPAN (2003)
Reoptimization of MDL keys for use in drug discovery
JL Durant et al.
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES (2002)
Chemography: The art of navigating in chemical space
TI Oprea et al.
JOURNAL OF COMBINATORIAL CHEMISTRY (2001)