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Computing preimages of Boolean networks.

Klotz J, Bossert M, Schober S - BMC Bioinformatics (2013)

Bottom Line: In this paper we present an algorithm based on the sum-product algorithm that finds elements in the preimage of a feed-forward Boolean networks given an output of the network.Our probabilistic method runs in linear time with respect to the number of nodes in the network.We evaluate our algorithm for randomly constructed Boolean networks and a regulatory network of Escherichia coli and found that it gives a valid solution in most cases.

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ABSTRACT
In this paper we present an algorithm based on the sum-product algorithm that finds elements in the preimage of a feed-forward Boolean networks given an output of the network. Our probabilistic method runs in linear time with respect to the number of nodes in the network. We evaluate our algorithm for randomly constructed Boolean networks and a regulatory network of Escherichia coli and found that it gives a valid solution in most cases.

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Similarity of y and  versus tmax
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Figure 2: Similarity of y and versus tmax

Mentions: Then we evaluate the network , and measure the similarity between y and by counting the equal entries and divide them by the length of y. We did so for 100 networks of Type A and B, and set T = 100. The averaged results can be seen in Figure 2.


Computing preimages of Boolean networks.

Klotz J, Bossert M, Schober S - BMC Bioinformatics (2013)

Similarity of y and  versus tmax
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3750533&req=5

Figure 2: Similarity of y and versus tmax
Mentions: Then we evaluate the network , and measure the similarity between y and by counting the equal entries and divide them by the length of y. We did so for 100 networks of Type A and B, and set T = 100. The averaged results can be seen in Figure 2.

Bottom Line: In this paper we present an algorithm based on the sum-product algorithm that finds elements in the preimage of a feed-forward Boolean networks given an output of the network.Our probabilistic method runs in linear time with respect to the number of nodes in the network.We evaluate our algorithm for randomly constructed Boolean networks and a regulatory network of Escherichia coli and found that it gives a valid solution in most cases.

View Article: PubMed Central - HTML - PubMed

ABSTRACT
In this paper we present an algorithm based on the sum-product algorithm that finds elements in the preimage of a feed-forward Boolean networks given an output of the network. Our probabilistic method runs in linear time with respect to the number of nodes in the network. We evaluate our algorithm for randomly constructed Boolean networks and a regulatory network of Escherichia coli and found that it gives a valid solution in most cases.

Show MeSH
Related in: MedlinePlus