Supervised reconstruction of biological networks with local models

Motivation: Inference and reconstruction of biological networks from heterogeneous data is currently an active research subject with several important applications in systems biology. The problem has been attacked from many different points of view with varying degrees of success. In particular, pre...

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Bibliographic Details
Published inBioinformatics Vol. 23; no. 13; pp. i57 - i65
Main Authors Bleakley, Kevin, Biau, Gérard, Vert, Jean-Philippe
Format Journal Article
LanguageEnglish
Published England Oxford University Press 01.07.2007
Oxford Publishing Limited (England)
Oxford University Press (OUP)
Subjects
Algorithms
Artificial Intelligence
Bioinformatics
Computer Science
Computer Simulation
Life Sciences
Models, Biological
Pattern Recognition, Automated
Pattern Recognition, Automated - methods
Protein Interaction Mapping
Protein Interaction Mapping - methods
Proteome
Proteome - metabolism
Quantitative Methods
Signal Transduction
Signal Transduction - physiology
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Summary:Motivation: Inference and reconstruction of biological networks from heterogeneous data is currently an active research subject with several important applications in systems biology. The problem has been attacked from many different points of view with varying degrees of success. In particular, predicting new edges with a reasonable false discovery rate is highly demanded for practical applications, but remains extremely challenging due to the sparsity of the networks of interest. Results: While most previous approaches based on the partial knowledge of the network to be inferred build global models to predict new edges over the network, we introduce here a novel method which predicts whether there is an edge from a newly added vertex to each of the vertices of a known network using local models. This involves learning individually a certain subnetwork associated with each vertex of the known network, then using the discovered classification rule associated with only that vertex to predict the edge to the new vertex. Excellent experimental results are shown in the case of metabolic and protein–protein interaction network reconstruction from a variety of genomic data. Availability: An implementation of the proposed algorithm is available upon request from the authors. Contact: Jean-Philippe.Vert@ensmp.fr
Bibliography:ark:/67375/HXZ-DM1H63V0-9
To whom correspondence should be addressed.
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ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1367-4803
1367-4811
1460-2059
1367-4811
DOI:10.1093/bioinformatics/btm204