Abstract
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 [1]. This technology,
an extension of Boolean Networks [2], is able to capture the time-varying dependencies with deterministic probabilities for a series of sets of predictor functions.
an extension of Boolean Networks [2], is able to capture the time-varying dependencies with deterministic probabilities for a series of sets of predictor functions.
Original language | English |
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Pages (from-to) | 63 |
Number of pages | 2 |
Journal | BMC Systems Biology |
Volume | 1 |
Issue number | Suppl 1 |
DOIs | |
Publication status | Published - 2007 |
Event | BioSysBio 2007: Systems Biology, Bioinformatics and Synthetic Biology - Manchester, United Kingdom Duration: 11 Jan 2007 → 13 Jan 2007 |
Keywords
- gene expression profiles has
- biomedicine
- context sensitive
- boolean networks