Big Data from Pharmaceutical Patents: A Computational Analysis of Medicinal Chemists' Bread and Butter.
By Nadine Schneider, Daniel M. Lowe, Roger A. Sayle, M. Tarselli, Gregory A. Landrum. Journal of Medicinal Chemistry, 2016
329 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Computational Theory and Mathematics, Materials Chemistry
View Paper: https://www.semanticscholar.org/paper/2cbd95e58c600d6602c152990978964cbc8c9857
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Biomedical Engineering
In Computational Theory and Mathematics
- Kenneth Atz
- Philippe Schwaller
- Francesca Grisoni
- Gisbert Schneider
- Spyridon Dimitriadis
- Ross Irwin
- Jiazhen He
- Michael Moret
In Materials Chemistry
- Philippe Schwaller
- Francesca Grisoni
- Kenneth Atz
- Gisbert Schneider
- Spyridon Dimitriadis
- Ross Irwin
- Jiazhen He
- C. Bekas
Citations in the corpus
- Chemformer: a pre-trained transformer for computational chemistry (2021, positive): “For the direct synthesis prediction task we made use of the benchmark USPTO-MIT dataset [33], which contains approximately 470,000 reactions originally extracted from patents [34].”
- Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction Prediction (2018, methodology): “Bradshaw et. al. passed the reagent information as a context vector to [13] 15418 15418 - Non-public time split test set, reactions from 2017 taken from Pistachio database [37, 36] Preprocessing methods their model.”
- Leveraging molecular structure and bioactivity with chemical language models for de novo drug design (2023, methodology): “The CLM was pretrained on the pharmaceutical subset of the US patent database 34,68 .”