Sentence examples for large scale datasets from from inspiring English sources

This was achieved by harnessing the power of mining large scale datasets from OMIM and other databases.

Applying big data approaches, namely the creation of large scale datasets from existing resources, as well as data mining methods (i.e. those related to machine learning), to test hypotheses related to epidemiologic, multilevel conceptual models will likely have implications for improving understanding of disease etiology and prognosis.

The contract states: "The PhD student will gather large-scale datasets from a variety of different mass crowd events, such as music festivals, sporting events, etc".

The approach utilizes our basic understanding of the physical processes involved in volcanic arc formation to find intensive variables, such as specific heat and density, which can be used to quantitatively link and compare large-scale datasets from different disciplines.

Fu et al. [3] indicated that the main challenge for future music information retrieval systems is to be able to train the music classification systems for large-scale datasets from few labeled data.

We evaluate our approach on large-scale datasets from several microarray experiments and on a clustered genome-wide genetic interaction network using different biological knowledge bases.

Due to the availability of more and more large-scale datasets from modern pyro-sequencing techniques, high-throughput analysis methods for thousands of RNAs are needed.

Beyond its pivotal role as a technological carving board, yeast genomics continues to play an important role in demonstrating the power of combining, collating, and curating large-scale datasets from a variety of "omic" approaches.

We chose to compare with these methods because they have been shown to outperform various other methods and they have been employed in the analysis of large-scale datasets from TCGA and 1KGP.

67 The goal of this free and widely available online resource is to integrate a variety of large-scale datasets from eukaryotic pathogens and their hosts, and facilitate data interrogation in an easily accessible system.

Solutions for learning from large scale datasets, including kernel learning algorithms that scale linearly with the volume of the data and experiments carried out on realistically large datasets.