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This modelling technique specifies mathematical relationships between the genes based on linear regression models.
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We observed improved correlations between platforms when ranking the genes based on the significance level than with a fixed statistical cut-off.
Despite the presence of sufficient variation for the traits between the two parents, most of the gene based markers did not show polymorphism indicating the possibility of novel QTLs.
Indeed, when determining, for increasing numbers of genes (10-1,000 genes, increments of 10), the overlap between the highest ranked genes based on the p-values of the replicate measurements of either the ratio- or intensity based ANOVA models, we observed a substantial proportion of reproduced genes in the intensity model.
We then compute the similarity between two genes based on the overlap between their GO profiles.
We rebuilt the phylogenetic relationships between PRDM genes based on the multiple alignment of the PR-domain of all PRDM proteins identified in vertebrates.
Kappa statistics were used to measure the similarities between genes based on their mapping profiles (rows of mapping profile matrix M in Fig. 3) (Dennis et al., 2003).
Second, we align the time samples for the target gene based on the time delays (see Algorithm 2), and compute correlations between this gene and the other genes based on the aligned samples.
Reverse engineering is the process of finding the regulatory relationships between genes based on DNA microarray data.
This set of assumptions has also been made when inferring functional variability from phylogenetic tree distances between OR genes based on the entire protein sequence (e.g., [14]).
Clusters were formed based on the phenotype similarities, and the similarity between pairs of genes based on their phenotype annotations using a Jaccard coefficient (the ratio of shared phenotypes over the unique set of phenotypes assigned to both the genes).
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Justyna Jupowicz-Kozak
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