Yu, Le and Marshall, Stephen (2007) Inferring context-sensitive probablistic boolean networks from gene expression data under multi-biological conditions. [Proceedings Paper]
In recent years biological microarrays have emerged as a high-throughput data acquisition technology in bioinformatics. In conjunction with this, there is an increasing need to develop frameworks for the formal analysis of biological pathways. A modeling approach defined as Probabilistic Boolean Networks (PBNs) was proposed for inferring genetic regulatory networks . This technology, an extension of Boolean Networks , is able to capture the time-varying dependencies with deterministic probabilities for a series of sets of predictor functions.
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