QSAR Applicability Domain Estimation by Projection of the Training Set in Descriptor Space: A Review
Procter & Gamble (Belgium) · Procter & Gamble (United States) · +2 more institutions
Abstract
As the use of Quantitative Structure Activity Relationship (QSAR) models for chemical management increases, the reliability of the predictions from such models is a matter of growing concern. The OECD QSAR Validation Principles recommend that a model should be used within its applicability domain (AD). The Setubal Workshop report provided conceptual guidance on defining a (Q)SAR AD, but it is difficult to use directly. The practical application of the AD concept requires an operational definition that permits the design of an automatic (computerised), quantitative procedure to determine a models AD. An attempt is made to address this need, and methods and criteria for estimating AD through training set…
Citation impact
- FWCI
- 4.17
- Percentile
- 100%
- References
- 29
Authors
3- JJJoanna JaworskaCorresponding
Procter & Gamble (Belgium), Procter & Gamble (United States)
- NNNina Nikolova-Jeliazkova
Bulgarian Academy of Sciences, Institute for Parallel Processing
- TATom Aldenberg
Topics & keywords
- Estimation
- Domain (mathematical analysis)
- Projection (relational algebra)
- Training (meteorology)
- Set (abstract data type)
- Space (punctuation)
- Artificial intelligence
- Computer science
- Partnerships for the goals