A method for analyzing strain differences in acquisition of IV cocaine self-administration in mice
| Autor: | Jaime R. Robles, Patrick M. Beardsley, Edwin J. C. G. van den Oord, Cristina Vargas-Irwin |
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| Rok vydání: | 2005 |
| Předmět: |
Male
Computer science Cocaine related disorders Self Administration Bioinformatics Machine learning computer.software_genre Cocaine-Related Disorders Mice Cocaine Species Specificity Genetics Animals Genetics (clinical) Ecology Evolution Behavior and Systematics Probability Mice Inbred BALB C Mice Inbred ICR business.industry Strain (biology) Temporal database Large sample Disease Models Animal Artificial intelligence business computer |
| Zdroj: | Behavior genetics. 36(4) |
| ISSN: | 0001-8244 |
| Popis: | The techniques currently available for studying drug self-administration in animals offer the unique opportunity to carry out micro-analysis of initial episodes of drug use which are extremely difficult to obtain for human subjects. Nonetheless, traditional self-administration techniques do not allow a cost-effective output of large sample sizes needed for genetic analysis. Additionally, the statistical techniques that allow the integration of within-subject temporal data with genetic information are scant. We therefore propose a two-stage method for analyzing strain differences in dynamic phenotypes for a high-throughput version of the self-administration procedure. On a first phenotype-refinement stage, a change-point algorithm (Gallistel et al. (2004) Proc. Natl Acad. Sci. USA 101:13124-13131) was used to separate individual drug self-administration response curves into three distinct components. In a second stage, strains differences in these indexes were assessed. This two-stage approach is illustrated with drug self-administration data and through a computer simulation. |
| Databáze: | OpenAIRE |
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