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Otherwise, too many colors, shapes, and interconnections may cause difficulties in the comprehension of data, or some visual elements may be too complex to recognize.
The comprehension of data meanings assisted to theorize relationships and led to the recontexualization of data into findings (MM, ST) [ 22].
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Rapid advances in genome sequencing technology are putting our ability to view data far ahead of our comprehension of such data.
In addition, the analysis and comprehension of the data obtained by metabolomics is often integrated with data from genomic and proteomic experiments [ 102].
The analysis and comprehension of the data obtained require the use of bioinformatics, as well as the integration with data obtained from genomic and proteomic analyses.
Consequently, this mandates the requirement of a flexible visualization paradigm to ensure effective and efficient perception and comprehension of the data.
Three different analysis methods were applied in order to get full comprehension of the data.
http://www.bioconductor.org/: open source and open development software project for the analysis and comprehension of genomic data.
Bioconductor is an open source software project for the analysis and comprehension of genomic data based on a free statistical programming language R. Three procedures for preprocessing were employed: background adjustment with GCRMA, normalization with the Quantile method, and finally summarization with median polish procedure.
Bioconductor is an open source software project and repository of instruments for the analysis and comprehension of genomic data.
Bioconductor is a free, open-source and open-development software project for the analysis and comprehension of genomic data.
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