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Completing SBGN-AF networks by logic-based hypothesis finding. (English) Zbl 1402.92209
Fages, François (ed.) et al., Formal methods in macro-biology. First international conference, FMMB 2014, Nouméa, New Caledonia, September 22–24, 2014. Proceedings. Berlin: Springer (ISBN 978-3-319-10397-6/pbk). Lecture Notes in Computer Science 8738. Lecture Notes in Bioinformatics, 165-179 (2014).
Summary: This study considers formal methods for finding unknown interactions of incomplete molecular networks using microarray profiles. In systems biology, a challenging problem lies in the growing scale and complexity of molecular networks. Along with high-throughput experimental tools, it is not straightforward to reconstruct huge and complicated networks using observed data by hand. Thus, we address the completion problem of our target networks represented by a standard markup language, called SBGN (in particular, activity flow). Our proposed method is based on logic-based hypothesis finding techniques; given an input SBGN network and its profile data, missing interactions can be logically generated as hypotheses by the proposed method. In this paper, we also show empirical results that demonstrate how the proposed method works with a real network involved in the glucose repression of S. cerevisiae.
For the entire collection see [Zbl 1316.92006].

MSC:
92C42 Systems biology, networks
92-04 Software, source code, etc. for problems pertaining to biology
03B42 Logics of knowledge and belief (including belief change)
Software:
SBGN; SOLAR
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