Inference of Signal Transduction Networks from Double Causal Evidence View Full Text


Ontology type: schema:Chapter      Open Access: True


Chapter Info

DATE

2010-08-17

AUTHORS

Réka Albert , Bhaskar DasGupta , Eduardo Sontag

ABSTRACT

Here, we present a novel computational method, and related software, to synthesize signal transduction networks from single and double causal evidences. This is a significant and topical problem because there are currently no high-throughput experimental methods for constructing signal transduction networks, and because the understanding of many signaling processes is limited to the knowledge of the signal(s) and of key mediators’ positive or negative effects on the whole process. Our software NET-SYNTHESIS is freely downloadable from http://www.cs.uic.edu/∼dasgupta/network-synthesis/.Our methodology serves as an important first step in formalizing the logical substrate of a signal transduction network, allowing biologists to simultaneously synthesize their knowledge and formalize their hypotheses regarding a signal transduction network. Therefore, we expect that our work will appeal to a broad audience of biologists. The novelty of our algorithmic methodology based on nontrivial combinatorial optimization techniques makes it appealing to computational biologists as well. More... »

PAGES

239-251

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-60761-842-3_16

DOI

http://dx.doi.org/10.1007/978-1-60761-842-3_16

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1047134861

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20835804


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