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Definition of phenotypes and pathways demands very large datasets achieved by combining data from multiple studies.
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Top apparent accuracy, leave-one-out cross-validation performance, and optimal 'k' value for each dataset achieved by the combinatoric k-TSP algorithm.
For example, the model of Savage et al. (2010) performs integrative modelling of two datasets only, achieved by introducing a 'fused context' (in which the two datasets are modelled together via a product of likelihoods) in addition to two 'unfused contexts' in which the two datasets are modelled separately.
First, all the WGS datasets achieved high concordance rates of the genotypes with those genotyped by SNP microarrays31,32 (≥99.97%), which provides confidence in calling of common variants.
The model-fitting results are reported in Table 2; this shows that close matches to each of the three patient datasets were achieved by the simulator.
Creation of datasets was achieved by using the parameter scan task of COPASI tool [ 49].
The best overall performance in the classification of the nine proxy datasets was achieved by the transformed FIS based on the GOMF.
The best recall on both datasets was achieved by the dictionary-based method 2 with the section names from the training set and SecTag.
The most objective discrimination between false and true changes in a dataset was achieved by using a "spike-in" experimental procedure based on Affimetrix GeneChip technology [10], [11], [12].
Comparing the expression profiles produced when using de novo assemblies as the mapping reference versus using the H. sapiens CCDS dataset was achieved by using CLC Genomics Workbench to map paired-end Illumina to the CCDS unique gene set and to two of the de novo TAs.
Although this method is not feasible for large datasets, the power achieved by an all-pairs test is of relevance, as this is the upper bound for the power of our algorithm.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com