Home- Research
- Conferences
- Program & Schedule
- Location
- KM in R&D Workshop
- Sponsors & Exhibitors
- Call for Contributions
- Bursary Awards
- Poster Session
- Program 2007
- Knowledge Management Workshop
- ADMET
- Beger, R
- Cherkasov, A
- Contrera, J
- Helma, C
- Hopfinger, A
- Jamois, E
- Klon, A
- Madden, J
- Pelletier, D
- Poroikov, V
- Richard, A
- Tomaszewski, J
- Program 2006
- Photo Gallery
- Workshops & Training
- Program
- Exhibition
- Registration
- About
- Overview
- Contact
- Support
- Schedule
|
|
|
|
|
|
|
|
|
|
|
| About Anthony Klon (Pharmacopeia Drug Discovery) |
|
Doctor Anthony E. Klon received his B.S. in Biochemistry from the University of Washington in 1997. After graduation, he pursued graduate studies in the lab of Professor Stephen C. Harvey in the Department of Biochemistry and Molecular Genetics at the University of Alabama at Birmingham. His thesis research focused on modeling the structure and dynamics of high-density lipoprotein particles with an emphasis on the structure and function of apolipoprotein A-I bound to discoidal HDL particles. While pursuing his dissertation research, he also studied protein and small molecule x-ray crystallography with Dr. David W. Borhani at the Southern Research Institute where he solved the atomic resolution ternary structures of human dihydrofolate reductase complexed with lipophilic antifolates. After receiving his PhD in 2002, he pursued postdoctoral studies with Dr. John W. Davies in the Lead Discovery Center at the Novartis Institutes for Biomedical Research in Cambridge, Massachusetts. His postdoctoral work focused on the evaluation of high-throughput docking software against a variety of pharmaceutically relevant targets. While at Novartis, he developed novel methods of improving the scoring of docking results using a combination of machine learning algorithms and data fusion techniques. Since 2005 he has been a research scientist at Pharmacopeia in Princeton, New Jersey where he has supported a variety of drug discovery programs. His current research interests include virtual high-throughput screening techniques, modeling the dynamics of protein-ligand interactions and developing novel approaches for ADME property prediction.
|
|
Bayesian Modeling of Numerical Data for ADME Property Prediction
Anthony E. Klon, Pharmacopeia Drug Discovery
We have implemented a naïve Bayesian classifier which models continuous numerical data using a Gaussian distribution. Several cases of interest in the area of ADME prediction are presented demonstrating that this approach is superior to implementations of Bayesian classifiers that model chemical descriptors with numerical values as binary data. We demonstrate that this enhanced performance, when compared with other implementations is independent of the descriptor sets chosen. We also compare the performance of three implementations of naïve Bayesian classifiers with previously published models.
|
|
|
|
|
|
|
|
|
