Machine Learning of Partial Charges Derived from High-Quality Quantum-Mechanical Calculations

By Patrick Bleiziffer, Kay Schaller, Sereina Riniker. 2018

143 citations recorded by the source corpus.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Yunsie Chung
2. Esther Heid
3. William H. Green
4. Florence H. Vermeire
5. Shih-Cheng Li
6. Haoyang Wu
7. David E. Graff
8. Charles J. McGill

Citations in the corpus

• Chemprop: A Machine Learning Package for Chemical Property Prediction (2023, methodology): “19 The dataset comprises 130,267 moderate size organic molecules with elements of types C, H, N, O, S, P, F, Cl, Br, and I, curated from ZINC and ChEMBL databases.”