Sentence examples for datasets from the large from inspiring English sources

Exact(1)

There is the potential to answer these questions by re-examining the existing datasets from the large adjuvant studies, and work is planned to try and validate our results within the HERA trial.

Similar(59)

Moreover it concurrent with recent datasets from the large-scale genome and transcriptome analysis of barley [ 59] showing the HvDME transcript (MLOC_17707.1) present in Morex seedlings, developing tillers, immature flowers and 4 DAF embryos, and in seeds of 5 and 15 DAF.

This paper investigates the dynamic positioning of offshore vessels in managed ice conditions using a model-scale dataset from the large ice tank of the Hamburg Ship Model Basin.

The Integrative Multi-species Prediction [ 9, 10] webserver has collected over 2,000 microarray datasets from the NCBI Gene Expression Omnibus (GEO), large collection of biochemical experiments from the Database of Protein and Genetic Interactions (BioGRID), tissue-specificity and phenotype characterizations from The Zebrafish Model Organism Database (ZFIN) and other sources for seven organisms.

We compare networks from these two datasets and the large size of the SAFHS allowed us to subdivide it into two independent subsets of 620 individuals.

Structured coronal mass ejections, i.e. events with clear white-light fine structures, have been selected from the dataset of the large angle spectroscopic coronagraph during the period 1996 2002.

From the large datasets, we found that down-regulated genes were more abundant than up-regulated genes during soybean seed development.

In recent years computational approaches have been adopted by many researchers in cancer studies either as a part of large population data analysis or only for predicting most deleterious SNPs from the large datasets.

To evaluate the performance of the algorithm, k-fold cross-validation was used for the model trained from the large datasets, whereas Jackknife cross-validation was applied when the models were trained with less than 30 positives.

In brief, we synthesize large datasets of size N followed by randomly selecting (n = |Q |) from the large synthetic datasets.

We leverage a unique dataset from the Hawaii Medical Service Association, the largest insurer in Hawaii, that contains micro-level information on behavior of over 700,000 patients and over 1,000 primary care physicians.

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