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Using data providers to query datasets is done through a RESTful API.
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The proposed approach is largely motivated by the issues related to querying datasets by clinical researchers, governmental or non-governmental organizations in monitoring health care services to improve quality of care.
Summary: With the wide application of next-generation sequencing (NGS) techniques, fast tools for protein similarity search that scale well to large query datasets and large databases are highly desirable.
Additionally, different taxonomic assignment programs were tested to evaluate specificity and sensitivity of taxonomic assignations as well as the effect of removing sequences that were close to the query dataset in different taxonomic levels.
Fig. 11 StreamAligner accuracy evaluation to map different query datasets on (a) Chr1 and (b) Chr21.
In order to query these datasets, users must have some information about their content as well as some knowledge of a query language such as SPARQL.
In this article, we introduce Spark, a new cluster computing framework that can run applications up to 40× faster than Hadoop by keeping data in memory, and can be used interactively to query large datasets with sub-second latency.
These can be used to plot simple tracks, or to query other datasets (such as productivity measures) for corresponding information at that location and time.
Therefore, the identifier mismatch makes it difficult to query multiple datasets simultaneously.
The query example below illustrates how the service can be used to query across datasets with different IRI schemes.
2, 3 The seed network can then be used to query large datasets in order to identify additional molecules with putative relationships to seed genes.
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