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In order to manage the above process and the distribution of the data across the project team, the datasets were stored in a central online document repository.
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All of the datasets are stored in a data center with a gigabit network environment.
This approach ensures no information loss, since the datasets are stored according to their original definitions and classification schemes, but at the same time enables data comparison.
The dataset is stored on the Hadoop file system (HDFS), each chunk is 64 MB, and each data chunk has three copies.
(i) The remaining candidate variables in the dataset are stored in the local macro 'SearchB'.
The dataset is stored into a relationship database on MySQL platform, version 5.0.44, whereas all the necessary scripts to store and query the database were written in Perl v5.8.8 (built for i686-linux) object-oriented scripting language.
The dataset was stored in MySQL 5.0 http://www.mysql.com, and the web interface was built by PHP scripts http://www.php.net on Red Hat Linux, powered by an Apache server http://www.apache.org.org
Ye et al. [ 8] proposed a different method based on a sparse representation of de Bruijn graphs, where only a subset of k-mers present in the dataset are stored.
The dataset is stored in a relational form using MySQL 4.1.14, whereas all the necessary scripts to store and query the database were written in Perl v5.8.8 (built for i686-linux) object-oriented scripting language, making use of two non-standard libraries, EnsEMBL Perl, [ 13] and BioPerl [ 14].
The raw transcriptomic datasets were stored at Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo) with an accession number of GSE41699.
Data conversion first began by ensuring that all datasets were stored under a common.csv file type.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com