Model validation: local diagnosis, correction and when to quit
By Jane S. Richardson, Christopher J. Williams, B. Hintze, Vincent B. Chen, Michael G. Prisant, Lizbeth L. Videau, David C Richardson. 2018
31 citations recorded by the source corpus.
An overview is provided of current crystallographic model validation of proteins and RNA, both foundations and criteria, at all resolution ranges, together with advice on how to correct specific types of problems and when you should not try so hard that you are overfitting.
Subfields: 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.
In Materials Chemistry
- Paul D. Adams
- Pavel V. Afonine
- Randy J. Read
- T. C. Terwilliger
- Nigel W. Moriarty
- T. Croll
- Jane S. Richardson
- David C Richardson
In Molecular Biology
- Paul D. Adams
- Pavel V. Afonine
- Randy J. Read
- T. C. Terwilliger
- Nigel W. Moriarty
- T. Croll
- Jane S. Richardson
- David C Richardson
Citations in the corpus
- Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix (2019, background): “These restraints can prevent the model from degrading at low resolution when the conformation is approximately correct, but should be used with caution because they can result in an incorrect local conformation minimum when the model geometry is poor (Richardson et al., 2018).”
- Integrating model simulation tools and cryo‐electron microscopy (2022, methodology): “162,233,234 MolProbity is the most widely-used validation package for model assessment.”
- MolProbity: More and better reference data for improved all‐atom structure validation (2018, methodology): “A recent overview from a CCP4 Study Weekend presentation 17 gives our best current guidance on how to tackle rebuilding the different types of validation outliers, with examples, and advice on when to stop.”