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Reduced complexity of the sequence may be due to consistently repeating patterns in the natural sequence, such as the tendency to prefer the use of specific di- or tri-nucleotides, or higher order words, which are not conserved in the shuffled genomes, or constraints imposed by the presence of coding regions.
The first step is to reduce complexity of services.
Reducing the size of the database reduces complexity of other operations down the line.
This was done to reduce complexity of the study.
This reduced complexity in base space increases the number of non-unique sequence matches to the in silico bisulfite converted genome.
The use of cDNA libraries for NGS is another and frequently used approach to reduce complexity, avoid repetitive sequences and target coding sequences for SNP discovery.
Specifically, novel bioinformatic approaches were developed to reduce the complexity of sequence contigs and ultimately to identify SNPs within specific sub-genomes.
This reduces the complexity of sequence information that needs to be analyzed but allows a comprehensive view on genes expressed during cardiac regeneration in the newt.
As this combination of datasets is currently not available for human we generated a modified reference sequence from the human reference genome hg19 (limited to chromosomes 1 and 2 to reduce computation time without reducing complexity) by inserting a representative set of TE sequences at random locations, excluding already annotated TEs and regions of Ns.
Second, it reduces complexity by getting rid of loopholes.
FFTs reduce complexity by reducing the number of computations made.
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