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Large screening datasets were selected from PubChem [19] to represent a spread in terms of size and ratio of active to inactive compounds.
Three experimental datasets were selected from the NCBI Short Reads Archive SRAA), each representing a real world challenge.
Five published datasets were selected from ArrayExpress.
146 microarray datasets were selected from 21 different platforms.
The real RNAseq datasets were selected from The Cancer Genome Atlas (TCGA) [ 13, 14].
In this study, as same as our own microarray data, the multiple datasets were selected from the experimental platform GPL1261 and were normalized with the RMA algorithm.
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The datasets are selected from the Internet, based on various challenges of indoor and outdoor environments such as camera variation, lighting difference and shadow effect (Figure 5) The ground truth data were segmented manually with the help of Photoshop and Adobe after the effect.
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.
The best models of nucleotide substitution for each dataset were selected from the uncorrected and corrected Akaike Information Criterion, the Hannan and Quinn performance-based decision theory and Bayesian Information Criterion of Jmodeltest version 0.1 and TREEFINDER version October 2008 (Munich, Germany, distributed by its author at www.treefinder.de).
The protein dataset was selected from SCOP [ 16], release 1.67.
Previously reported gene expression datasets were selected and downloaded from the Gene Expression Omnibus database.
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