Sentence examples for retrieval pipeline from inspiring English sources

Fig. 7 Retrieval pipeline overview.

An overview of the geometry-aware retrieval pipeline is shown in Fig. 7.

NetVLAD mimics the standard image retrieval pipeline to provide robustness for translation and partial occlusion.

This might be due to the high confidence interval (C.I. 95%) applied during our PAGs retrieval pipeline, that might have led to a partial understimatation of the actual amount of atypical ORFs that are integrated on plasmids.

Pipelining the retrieval, the integration and the high-throughput investigation of such data in a fashion specifically tailored to the interests of the user should facilitate wider application by putting EST data in the hands of researchers directly addressing focused biological questions, without requiring the involvement of bioinformaticians.

In a final step, the pipeline retrieves the SMILES for the compounds using the PubChem Power User Gateway (PUG) REST service [57], a protocol preferred for the final step as it is optimized for the bulk retrieval of data [58].

The list of candidate genes has to be uploaded as a txt file and information retrieval is done using the pipeline described above (also including the gene count).

In the future we plan to define a set of process and event types for NGS management and integrate it with an NGS analysis pipeline, to automatize retrieval and storage of data on the Digital Biobank.

Indeed, applying the same pipeline for PAGs retrieval with lower CI thresholds allowed to assemble larger PAGS datasets (embedding 14731, 27201 and 38950 sequences at 70%, 80%and9090% CIs, respectively).

Consequently, text-mining is becoming an important component in the curation pipeline for the retrieval and extraction of biological information at curated databases (7), and has been shown to improve both the efficiency and accuracy of manual curation (8).

Finally, we discuss the performance of gene mention normalization provided by G nat. G nat consists of a set of modules to handle all steps required in a text processing pipeline, from document retrieval to named entity normalization.