Active user’s response: Lessons from the structure-activity relationship analysis of dopamine antagonists (2002) [1 citations — 1 self]
Abstract:
Mining SAR (structure-activity relationship) is a complex problem that is typical of those encountered mining data. A recent analysis of dopamine antagonist activity produced valuable models of the interactions between antagonists and dopamine receptors. The cascade model was used together with methods recently developed for datascape surveys. Two analysts collaborated in interpreting the rules generated, one of whom has had a long career in drug design with a pharmaceutical company. This paper briefly introduces the problem, the data source, how attributes were generated, and the tasks involved in rule interpretation. Some important hypotheses are described. We discuss how they are drawn from the rule expressions, what kind of data stimulated the analysts, and the necessary improvements to the method to facilitate the active response of analysts. 1.
Citations
| 5 | Efficient Detection of Local Interactions in the Cascade Model – Okada - 2000 |
| 4 | Characteristic substructures and properties in chemical carcinogens studied by the cascade model – Okada - 2003 |
| 3 | Discovery of Structure Activity Relationships using the Cascade Model: The Mutagenicity of Aromatic Nitro Compounds – Okada - 2001 |
| 3 | Datascape Survey using the Cascade Model – Okada - 2002 |
| 3 | Topographical Expression of a Rule for Active Mining – Okada - 2002 |
| 1 | Mining Characteristics of Lead Compounds using the Cascade Model – Okada, Yamakawa - 2002 |
