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This equation (1) was used to predict the melting temperatures for a test dataset of 225 oligonucleotide sequences whose experimental melting temperatures were known; (Figure 1), where a correlation coefficient (r) of 0.99 and an average error of 1.31°C was obtained (data provided in Table S2).
Specifically, we score an HMM probabilistically by its likelihood for a test dataset of MD trajectories.
A test dataset of 97 randomly selected mechanism of injury only records was used for a trial linkage with the VEMD.
We then validated the models on a test dataset of 56,392 genomic locations (6632 p63-positive sites and 49760 p63-negative sites).
For the purpose of evaluation of the five methods employed, a test dataset of Pfam families with known structure and SCOP domain information was generated.
The resulting HMM-based modeling framework evaluates the model quality by the likelihood of a model given a test dataset of simulation trajectories.
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We used experimentally determined or known CP and CM proteins of Gram-negative bacteria previously performed in the evaluation of PSORTb as a test dataset for validation of the LDA based classifier's performance [ 27].
For a performance evaluation of our prototype we used a test dataset consisting of values taken from the list of Medical Subject Headings (MeSH) [25].
This dataset is divided into two parts: (i) A training set consisting of 123 oligomers for obtaining the best fit equation giving the minimum possible error and (ii) a test dataset consisting of 225 oligomers, to assess the quality of prediction on independent data.
Evaluation of the method was done on a test dataset consisting of 24 FOVs from all defined compartments and patient groups.
The benchmarking using a test dataset comprising of both known T2D genes and non-T2D genes revealed that Wv method had a sensitivity and specificity of 0.74 and 0.96 respectively with 9 fold enrichment.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com