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Recently, Islamaj Doğan and Lu (2012b) successfully built a rule-based inference method with application to disease name normalization to MeSH and OMIM terminology.
ABC, its position in the ensemble of model-based inference methods, and its application in evolutionary genetics are reviewed in Marjoram et al. (2003), Beaumont and Rannala (2004), Marjoram and Tavaré (2006), Beaumont (2010), Bertorelle et al. (2010), and Csilléry et al. (2010).
While many simplifications were made in the application of the inference method presented here, the method has potential to be extended in several directions.
A GRN, then, is defined as a network that has been inferred from gene expression data by the application of a statistical inference method [ 7, 34].
Application of more than one taxonomy inference method is likely to improve the reliability of GMMS and other taxonomy-based network reconstruction tools.
The comparison between Method 2 and Method 1 demonstrated that the application of bootstrapping in order to select the highest scored haplotype inference (Method 2) gives better results than the method without bootstrapping (Method 1).
We present an inference method that works in this case.
Takagi Sugeno Inference method is used in the ANFIS model.
The inference methodology used is the Mamdani inference method.
Therefore, an approximate inference method is required.
b) Prior use of an inference method.
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