OnionTree provides an XML format to encode biological relationships as prior knowledge within a Bayesian scheme. An OnionTree XML file contains a dictionary for a set of objects, a set of Boolean expressions on those objects, and statements about the expressions that encode probabilities on relationships between the expressions. In this way, prior knowledge, such as exclusivity of mutations within a pathway, can be encoded as prior conditional probabilities.
For instance, we can say that the probabilty to carry a mutation is 0.1 for each of the proteins in a pathway by writing statements encoding P(Xi)=0.1. The probability that at least one of the proteins carries a mutation should be quite high (say 0.9) if an event P happens: p (X | P) = 0.9 where X is defined as a union of all the Xi 's. Similar statements can be made for many types of high-thoughput biological data.
This is the schema of the language.
A. Favorov, D. Lvovs, W. Speier, G. Parmigiani, and M. F. Ochs, “OnionTree XML: A Format to Exchange Gene-Related Probabilities.,” Journal of Biomolecular Structure & Dynamics, vol. 29, no. 2, pp. 417-23, Oct. 2011
The language is designed by: Alexander Favorov1,2,Dmitrijs Lvovs2,William Speier1,Giovanni Parmigiani3 and Michael F. Ochs1
1Oncology Biostatistics and Bioinformatics, Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD, USA
2Laboratory of Bioinformatics, Research Institute for Genetics and Selection of Industrial Microorganisms, Moscow, RF
3Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, MA, USA
The image representing the Onion Tree XML structure is created by XSD Diagram schema definition diagram viewer
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