Predicting the outcomes of organic reactions via machine learning: are current descriptors sufficient?

Computer-Assisted Synthetic Planning: The End of the Beginning

(2016) Sara Szymkuć et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Machine-learning-assisted materials discovery using failed experiments

(2016) Paul Raccuglia et al.   NATURE

The Harvard organic photovoltaic dataset

(2016) Steven A. Lopez et al.   Scientific Data

A Priori Estimation of Organic Reaction Yields

(2015) Fateme S. Emami et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Development of a Novel Fingerprint for Chemical Reactions and Its Application to Large-Scale Reaction Classification and Similarity

(2015) Nadine Schneider et al.   Journal of Chemical Information and Modeling

Economic reasoning and artificial intelligence

(2015) D. C. Parkes et al.   SCIENCE

Machine learning: Trends, perspectives, and prospects

(2015) M. I. Jordan et al.   SCIENCE

Regularization Paths for Generalized Linear Models via Coordinate Descent

(2015) Jerome Friedman et al.   Journal of Statistical Software

Organic Chemistry as a Language and the Implications of Chemical Linguistics for Structural and Retrosynthetic Analyses

(2014) Andrea Cadeddu et al.   ANGEWANDTE CHEMIE-INTERNATIONAL EDITION

Computer science: The learning machines

(2014) Nicola Jones   NATURE

Deep Architectures and Deep Learning in Chemoinformatics: The Prediction of Aqueous Solubility for Drug-Like Molecules

(2013) Alessandro Lusci et al.   Journal of Chemical Information and Modeling

The big challenges of big data

(2013) Vivien Marx   NATURE

Big (chemistry) data

(2013) Bruce C. Gibb   Nature Chemistry

Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups

(2012) Geoffrey Hinton et al.   IEEE SIGNAL PROCESSING MAGAZINE

ReactionPredictor: Prediction of Complex Chemical Reactions at the Mechanistic Level Using Machine Learning

(2012) Matthew A. Kayala et al.   Journal of Chemical Information and Modeling

Application of Molecular Topology for the Prediction of Reaction Yields and Anti-Inflammatory Activity of Heterocyclic Amidine Derivatives

(2011) Jordi Pla-Franco et al.   INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES

Predicting a small molecule-kinase interaction map: A machine learning approach

(2011) Fabian Buchwald et al.   Journal of Cheminformatics

Image processing and machine learning for fully automated probabilistic evaluation of medical images

(2010) Luka Šajn et al.   COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE

Application of molecular topology for the prediction of the reaction times and yields under solvent-free conditions

(2010) Jorge Gálvez et al.   GREEN CHEMISTRY

Ranking Chemical Structures for Drug Discovery: A New Machine Learning Approach

(2010) Shivani Agarwal et al.   Journal of Chemical Information and Modeling

A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data

(2009) Bjoern H Menze et al.   BMC BIOINFORMATICS

Machine Learning for In Silico Virtual Screening and Chemical Genomics: New Strategies

(2008) Jean-Philippe Vert et al.   COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING

The future of biocuration

(2008) Doug Howe et al.   NATURE