Sentence examples for genomic data processing from inspiring English sources

Here we focused on three areas of interest: medical image analysis, physiological signal processing, and genomic data processing.

For daily use, general purpose compression tools, such as gzip, may continue to play an important role in the context of genomic data processing, mainly due to its pervasiveness and relatively good speed.

Database URL: BioDIG website: http://biodig.org BioDIG source code repository: http://github.com/FriedbergLab/BioDIG The MyDIG database: http://mydig.biodig.org/ The large amount of genomic data has led to a concurrent deluge of new and creative ways of genomic data processing and visualization.

Individual array files (74 total) were uploaded in ArrayTrack [ 38, 39], the Food and Drug Administration's relational database for genomic data storage, processing, analysis, and visualization that was created at the NCTR.

SampleNetwork has been designed to facilitate detailed exploration of sample relationships and expedite genomic data pre-processing decisions via sample network analysis.

Interfaces are available for processing genomic data from the GenBank database [ 25], RAST [ 26], or the DOE KnowledgeBase [ 27].

The Ensembl system (Hubbard et al., 2002) is an example of a complete platform for processing genomic data, but it was custom built for the needs of the Sanger Institute rather than a community software.

The others are about processing of large genomic data from 'Workshop on Parallel and Distributed Processing of Large Genome Data' [ 82].

The technology-dependent modules for microarray data (Refiner Array), mass spectrometry (Refiner MS, used in the present study) and genomic profiling (Refiner Genome) allow highly-sophisticated data processing, quantification, visualization, and result exporting in any generally-used formats.

Most data processing and genomic analyses of large-scale sequencing data are conducted on high-performance computing clusters running a UNIX-based operating system.

Whether large datasets will significantly improve the ability of clustering methods to detect existing structure when genetic differentiation is small remains to be tested with recent programs that have been specifically developed for rapidly processing population genomic data (Popescu et al. 2014; Raj et al. 2014).