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Although these genes have been well studied because of their medical importance, we demonstrate that a large amount of sequence variation has not yet been described.
De novo assembly has been performed for the transcriptome analysis, function annotation and development of numerous markers in various plants (Parchman et al. 2010; Wang et al. 2010; Oliver et al. 2011) including pepper to rapidly generate a large amount of sequence data (Lu et al. 2011 2012; Ashrafi et al. 2012; Go'ngora-Castillo et al. 2012; Hill et al. 2013; Liu et al. 2013).
The large amount of sequence data available has created the field of genomics, research that uses computational tools to search for and analyze patterns in the full genomes of organisms.
This was likely also affected by the large amount of sequence data available.
If we had the same, large amount of sequence information for all structures, we might find most structures to be functionally versatile; and we might find most functions to be executable by multiple structures.
Given the large amount of sequence information currently available in databases of biological proteins, this method can be extremely effective at profiling amino acid positions determined by natural selection.
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We further show how to interpret and analyze the large amount of sequencing data that is generated in RNA-seq.
The power of large-scale sequencing techniques not only lies in the large amount of sequencing throughput but also in the possibility to gain multi-faceted data of genomic, epigenomic and transcriptomic origin.
Moreover, the analysis of large amount of sequencing data generated for each sample remains quite challenging.
It also requires that a large amount of sequencing be performed before estimates can be generated.
The inputs of CUDA-SWf are a query sequence and a specific protein database with a large amount of sequences.
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