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A simple pattern classification method for alcohol-responsive proteins that are differentially expressed in mouse brain.

Abstract

Proteomic analysis of brain tissues obtained from two inbred mice, C57BL/6J (B6, an alcohol-preferring strain) and DBA/2J (D2, an alcohol-avoiding strain), that were orally administered 1.5 g/kg ethanol, was performed to investigate alcohol-responsive proteins. To analyze relationships of alcohol-responsive protein spots between B6 and D2 mice, we have developed a simple spot classification method (SCM) for the fully matched spot data sets produced by the Melanie 4 analysis software using the paired two-dimensional (2-D) gels of two strains over time. By applying SCM, 55 protein spots that were differentially expressed in brain tissue were classified into 16 patterns as mirror images (2x8 patterns), and additionally in an ordered fashion such as 'fast turn over' and 'slow turn over' forms, depending on the frequency of repetition and rate of changed expression profile in 2-D gels over time. Searching for any interaction proteins through databases of interacting proteins using the classified data set has led to the construction of a linkage map, which reveals the interrelationship of the alcohol-responsive proteins between different species. Thus, it is suggested that the different responses for alcohol between B6 and D2 may come from differences of the response rates and interactions of different variants of the alcohol-responsive protein family.

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BibTeXRIS

Bokyung Park, Seul-Ki Jeong, Won-Suk Lee, Je Kyung Seong, Young-Ki Paik. 2004. A simple pattern classification method for alcohol-responsive proteins that are differentially expressed in mouse brain.. https://doi.org/10.1002/pmic.200400958

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