volume 5, issue 10, Pe13397 2010
DOI: 10.1371/journal.pone.0013397
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Abstract: BackgroundCurrent technologies have lead to the availability of multiple genomic data types in sufficient quantity and quality to serve as a basis for automatic global network inference. Accordingly, there are currently a large variety of network inference methods that learn regulatory networks to varying degrees of detail. These methods have different strengths and weaknesses and thus can be complementary. However, combining different methods in a mutually reinforcing manner remains a challenge.MethodologyWe …

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