Abstract
High-throughput screening (HTS) is an efficient technological tool for drug discovery in the modern pharmaceutical industry. It consists of testing thousands of chemical compounds per day to select active ones. This process has many drawbacks that may result in missing a potential drug candidate or in selecting inactive compounds. We describe and compare two statistical methods for correcting systematic errors that may occur during HTS experiments. Namely, the collected HTS measurements and the hit selection procedure are corrected.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
BRIDEAU, C., GUNTER, B., PIKOUNIS, W. and LIAW, A. (2003): Improved statistical methods for hit selection in high-throughput screening. Journal of Biomolecular Screening, 8, 634–647.
ELOWE, N.H., BLANCHARD, J.E., CECHETTO, J.D. and BROWN, E.D. (2005): Experimental screening of dihydrofolate reductase yields a “test set” of 50,000 small molecules for a computational data-mining and docking competition. Journal of Biomolecular Screening, 10, 653–657.
HEUER, C., HAENEL, T., PRAUSE, B. (2003): A novel approach for quality control and correction of HTS data based on artificial intelligence. The Pharmaceutical Discovery & Development Report. PharmaVentures Ltd. [Online].
HEYSE, S. (2002): Comprehensive analysis of high-throughput screening data. In: Proceedings of SPIE 2002, 4626, 535–547.
KAUL, A. (2005): The impact of sophisticated data analysis on the drug discovery process. Business Briefing: Future Drug Discovery 2005. [Online]
KEVORKOV, D. and MAKARENKOV, V. (2005): Statistical analysis of systematic errors in HTS. Journal of Biomolecular Screening, 10, 557–567.
MAKARENKOV, V., KEVORKOV, D., GAGARIN, A., ZENTILLI, P., MALO, N. and NADON, R. (2006): An efficient method for the detection and elimination of systematic error in high-throughput screening. Submitted.
ZHANG, J.H., CHUNG, T.D.Y. and OLDENBURG, K.R. (1999): A Simple Statistic Parameter for Use in Evaluation and Validation of High Throughput Screening Assays. Journal of Biomolecular Screening, 4, 67–73.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin · Heidelberg
About this paper
Cite this paper
Gagarin, A., Kevorkov, D., Makarenkov, V., Zentilli, P. (2006). Comparison of Two Methods for Detecting and Correcting Systematic Error in High-throughput Screening Data. In: Batagelj, V., Bock, HH., Ferligoj, A., Žiberna, A. (eds) Data Science and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-34416-0_26
Download citation
DOI: https://doi.org/10.1007/3-540-34416-0_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34415-5
Online ISBN: 978-3-540-34416-2
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)