- Title
- Hybrid Scoring and Classification Approaches to Predict Human Pregnane X Receptor Activators
- Creators
- Sandhya KORTAGERE - Department of Pharmacology and Environmental Bioinformatics and Computational Toxicology Center (ebCTC), University of Medicine and Dentistry of New Jersey (UMDNJ)-Robert Wood Johnson Medical School, 675 Hoes lane, Piscataway, NJ 08854, United StatesDmitriy CHEKMAREV - Department of Pharmacology and Environmental Bioinformatics and Computational Toxicology Center (ebCTC), University of Medicine and Dentistry of New Jersey (UMDNJ)-Robert Wood Johnson Medical School, 675 Hoes lane, Piscataway, NJ 08854, United StatesWilliam J WELSH - Department of Pharmacology and Environmental Bioinformatics and Computational Toxicology Center (ebCTC), University of Medicine and Dentistry of New Jersey (UMDNJ)-Robert Wood Johnson Medical School, 675 Hoes lane, Piscataway, NJ 08854, United StatesSean EKINS - Department of Pharmacology and Environmental Bioinformatics and Computational Toxicology Center (ebCTC), University of Medicine and Dentistry of New Jersey (UMDNJ)-Robert Wood Johnson Medical School, 675 Hoes lane, Piscataway, NJ 08854, United States
- Publication Details
- Pharmaceutical research, v 26(4), pp 1001-1011
- Publisher
- Springer; New York, NY
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Microbiology and Immunology
- Web of Science ID
- WOS:000263799000025
- Scopus ID
- 2-s2.0-61349196018
- Other Identifier
- 991014877775504721
Journal article
Hybrid Scoring and Classification Approaches to Predict Human Pregnane X Receptor Activators
Pharmaceutical research, v 26(4), pp 1001-1011
2009
PMID: 19115096
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- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Chemistry, Multidisciplinary
- Pharmacology & Pharmacy