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The dataset is selected in the first wizard step (see Figure 2).
The "standard" complex-protein dataset is selected in terms of best accuracy and coverage in a set of manually-curated complexes, but there can be other possible variations of complex-protein sets if the threshold of accuracy and coverage for clustering becomes more flexible.
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The 205 genes appearing in this dataset were selected in Yeung et al. (2003) to reflect four functional Gene Ontology (GO) categories.
Here, the most appropriate classifier, features, discretization algorithm, adjustment method for missing data, and derivation dataset are selected in order to develop the highest performing predictive models.
Once a group of datasets is selected in the follow-up analysis pipelines, the software automatically prompts available expression genotype pairs for the user to choose from.
The datasets were selected in respect to have a rather unspecific regulation, i.e. from treatments affecting not a small band but a broad range of metabolic pathways.
The datasets were selected, in the first instance, because of the quality of the data, both expression and accompanying clinical data.
The viruses that belong to the Primate lentivirus group, which could be displayed as the representation of the HIV in our dataset, were selected out and integrated in Figure 2. As shown in the molecular function tree, almost all HIV-1 and HIV-2 viruses were divided into two categories (GO terms of human proteins that correspond to separate HIV-1 and HIV-2 are stored in Additional file 1).
To create the first series in the benchmark, the first assay in the dataset was selected and an attempt was made to find a set of 5 molecules whose activities differ by at least 0.38 log units (this attempt involved iterating randomly over all possible selections of 5 molecules from the assay several thousand times).
Best-fit evolutionary models for each individual gene fragment (in the partitioned dataset) as well as unpartitioned dataset were selected based on Akaike Information Criterion implemented in jModelTest v0.1.1 [ 38, 41].
The 1640 proteins in this dataset were selected from PDB based on the following criteria: (1). the structures are obtained by X-ray experiment, (2). the resolution should be lower than 2 Å, (3) the proteins do not contain any small molecule ligands, (4). the proteins are asymmetric, and (5) the proteins do not contain any modified residue.
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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