Cargando…
Assessment of Prediction Confidence and Domain Extrapolation of Two Structure–Activity Relationship Models for Predicting Estrogen Receptor Binding Activity
Quantitative structure–activity relationship (QSAR) methods have been widely applied in drug discovery, lead optimization, toxicity prediction, and regulatory decisions. Despite major advances in algorithms and software, QSAR models have inherent limitations associated with a size and chemical-struc...
Autores principales: | Tong, Weida, Xie, Qian, Hong, Huixiao, Shi, Leming, Fang, Hong, Perkins, Roger |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
National Institute of Environmental Health Sciences
2004
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1277118/ https://www.ncbi.nlm.nih.gov/pubmed/15345371 http://dx.doi.org/10.1289/txg.7125 |
Ejemplares similares
-
Using Decision Forest to Classify Prostate Cancer Samples on the Basis of SELDI-TOF MS Data: Assessing Chance Correlation and Prediction Confidence
por: Tong, Weida, et al.
Publicado: (2004) -
Phenotypic Anchoring of Gene Expression Changes during Estrogen-Induced Uterine Growth
por: Moggs, Jonathan G., et al.
Publicado: (2004) -
Prediction of Toxicant-Specific Gene Expression Signatures after Chemotherapeutic Treatment of Breast Cell Lines
por: Troester, Melissa A., et al.
Publicado: (2004) -
Genome-wide mapping and analysis of aryl hydrocarbon receptor (AHR)- and aryl hydrocarbon receptor repressor (AHRR)-binding sites in human breast cancer cells
por: Yang, Sunny Y., et al.
Publicado: (2017) -
Gene Interaction Network Suggests Dioxin Induces a Significant Linkage between Aryl Hydrocarbon Receptor and Retinoic Acid Receptor Beta
por: Toyoshiba, Hiroyoshi, et al.
Publicado: (2004)