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In comparison, the Gaussian model eliminated all targets as non-significant, while the fold-change method inferred the same 10 targets as our method, but also inferred an additional 8 targets, none of which have evidence of binding SB-202190 (Figure 4a and Table S1).
For example, species tree inference from a set of 106 genes in 8 yeast species required 800 h using Bayesian estimation on a coalescent model, whereas a parsimony method inferred the identical tree in only a 'fraction of a second' (Than and Nakhleh, 2009).
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After finding optima for each class based on the probability measure PM (defined in Equation (6)), the method infers the class of the analysed blob also using the reliability measure PM.
The method infers the localities of the tree nodes by maximum parsimony, and by Monte Carlo simulation tests the significance of migration events that accrue back and forth between all pairs of localities over time.
However, compared to these methods, our proposed method infers the highest number of correct predictions.
This method infers the codon reading assignment in eukaryotes from genomic data.
In this paper, we propose a two-step method: infer the activity profiles of a TF in the cell cycle and then test the significance of its periodicity.
This method infers the contemporary effective population size from estimated sibship frequencies, drawing on the idea that a smaller population will result in a higher proportion of sibs in any given random sample.
Both methods inferred the same root for each data set.
Moreover, both ML and Bayesian-based methods inferred the same root for the tree.
In each case, ML and Bayesian methods inferred the same topology.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com