BMC research notes · 2010
aeGEPUCI: a database of gene expression in the dengue vector mosquito, Aedes aegypti.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Dissanayake Sumudu N, Ribeiro Jose Mc, Wang Mei-Hui, Dunn William A, Yan Guiyun, James Anthony A, Marinotti Osvaldo
Аннотация
BACKGROUND: Aedes aegypti is the principal vector of dengue and yellow fever viruses. The availability of the sequenced and annotated genome enables genome-wide analyses of gene expression in this mosquito. The large amount of data resulting from these analyses requires efficient cataloguing before it becomes useful as the basis for new insights into gene expression patterns and studies of the underlying molecular mechanisms for generating these patterns.
FINDINGS: We provide a publicly-accessible database and data-mining tool, aeGEPUCI, that integrates 1) microarray analyses of sex- and stage-specific gene expression in Ae. aegypti, 2) functional gene annotation, 3) genomic sequence data, and 4) computational sequence analysis tools. The database can be used to identify genes expressed in particular stages and patterns of interest, and to analyze putative cis-regulatory elements (CREs) that may play a role in coordinating these patterns. The database is accessible from the address http://www.aegep.bio.uci.edu.
CONCLUSIONS: The combination of gene expression, function and sequence data coupled with integrated sequence analysis tools allows for identification of expression patterns and streamlines the development of CRE predictions and experiments to assess how patterns of expression are coordinated at the molecular level.
FINDINGS: We provide a publicly-accessible database and data-mining tool, aeGEPUCI, that integrates 1) microarray analyses of sex- and stage-specific gene expression in Ae. aegypti, 2) functional gene annotation, 3) genomic sequence data, and 4) computational sequence analysis tools. The database can be used to identify genes expressed in particular stages and patterns of interest, and to analyze putative cis-regulatory elements (CREs) that may play a role in coordinating these patterns. The database is accessible from the address http://www.aegep.bio.uci.edu.
CONCLUSIONS: The combination of gene expression, function and sequence data coupled with integrated sequence analysis tools allows for identification of expression patterns and streamlines the development of CRE predictions and experiments to assess how patterns of expression are coordinated at the molecular level.