Algorithms for Inference of Genetic Networks (AIGNET)
نویسندگان
چکیده
Powerful new technologies, such as DNA microarrays, provide simple and economical ways to explore gene expression patterns on a genomic scale[1, 2]. Using comprehensive gene expression data, various approaches are planned to infer genetic networks [3, 4]. In this poster, we propose a system named AIGNET (Algorithms for Inference of Genetic Networks), and introduce two top down approaches for inference of genetic networks, which rely on the analysis of state changes and/or temporal responses of gene expression patterns. We show the strategy is exible and rich in structure.
منابع مشابه
AIGNET: A System That Infers Large Scale Genetic Networks
Recent advances of technology in bioinformatics have made gene expression comprehensive and several approaches have been proposed to infer the genetic networks, using such gene data [2, 3]. We previously proposed a system named AIGNET (Algorithms for Inference of Genetic Networks) in which either of two completely different network models work independently [4]. One model is a static Boolean ne...
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