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The datasets generated from the Tennessee Eastman process (TEP) simulator were used to evaluate the classification performance.
We present a realistic test of the new method by classifying large chemical datasets generated from the ChEMBL database [4].
It is thus paramount to develop and employ effective machine learning techniques to deal with such high dimensional and large datasets generated from the CAS area.
The x-axis of the graph is shown on log-scale and it represents the size of clusters in the case of the pseudo-clustering datasets generated from the WOMBAT and PubChem MLSMR datasets.
Comparison of AD-associated methylation changes between two datasets generated from the STG.
We prepared simulated datasets generated from the E. coli genome to evaluate effectiveness of the EA algorithm.
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The ClueWeb1 dataset is another semi-synthetic dataset generated from the original ClueWeb dataset.
The BigCross dataset is a semi-synthetic dataset generated from the real-world BigCross dataset.
The ClueWeb dataset is a semi-synthetic dataset generated from the ClueWeb Category B dataset.
To further decipher the relationship between these subunits, we examined another proteomic dataset generated from the chromatographic fractionation of the Rpd3L and Rpd3S complexes isolated from wild-type and four deletion strains followed by Rpd3-TAP purification (Table S3) [5].
The dataset generated from the expression analysis, along with quality control data and the numbers of genes altered are provided in Supplementary Table 1 (Table S1) and Supplementary Fig. 1 (Figure S1).
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CEO of Professional Science Editing for Scientists @ prosciediting.com