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If D is the maximal number of branches to which a Fork can lead to, then the optimal solution for the SLA free problem can be computed in O (h.D.(S+ 2.(m log m)) where h is the depth of the sequence.
The time required to access the corresponding information measures the logical depth of the sequence.
This metric combines both the depth of the sequence alignments with the mean identity of the aligned reads.
Building upon this foundation, varDB will expand the breadth and depth of the sequence coverage as well as specific tools for the analysis of antigenic variation.
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It is commonly accepted that the depth of the sequencing can affect the results of an analysis [ 25– 28].
The average mapping depth of the sequencing data was approximately 14-fold, which is sufficient for accurate VB-based analysis.
This uncertainty can always be minimized by increasing the depth of the sequencing to reduce the variation in these coverage level fluctuations.
Depending on the depth of the sequencing there is a different number of reads covering each CpG site (i.e. reads coverage).
In general, the resolution of non-invasive tumor genome-wide scans from plasma is limited by the depth of the sequencing and the percentage of tumor fragments in the plasma.
Finally, the depth of the sequencing reads needs to be comparable as tag counts at each peak and even the number of peaks will be proportional to the total tags sequenced.
The contig coverage described here is different from the read coverage which is approximate coverage of the genome from the sampled reads and represents the sequencing depth of the source sequences in the datasets.
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CEO of Professional Science Editing for Scientists @ prosciediting.com