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The aforementioned SNVs annotation led us to set up a new bioinformatics method, that we termed g-deNoise, to efficiently filter polymorphic multialigned reads generated from virtual and experimental sequencing data.
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Experimental sequence data were analysed and assembled with CodonCode Aligner (http://www.codoncode.com/aligner) and the contig containing good quality sequences was compared with the sequences available at the non-redundant database at NCBI using BLASTX.
Since every data point is tested exactly once, it has been a widely used evaluation method for real experimental sequence data, (just as the case in gp120 benchmark experiment) [ 37- 42].
CRB was responsible for experimental design, sequencing, data analysis, and discussion.
XL and JL were involved in the planning and design of the study, performed the experimental work, sequencing data analysis and statistical analysis, and drafted the manuscript.
The terminal, penultimate, complex-participation and complex-dissociation models were each tested for applicability to the mechanism of copolymerization for this comonomer system by applying reactivity ratio related test functions to the experimental sequence distribution data, enabling a direct visual assessment of the applicability of each model to be made.
For proteins not belonging to sufficiently large or diverse families but for which functional selections have been developed, it should be possible to develop experimental sequence covariation data sets by library generation, functional selection, and next generation sequencing.
We have redefined the binding motifs of GlnR and TnrA on basis of the available experimental and sequence data and used them to identify their respective regulons anew.
Indeed, when the distribution resembles the 'predicted' organelle distribution from experimental or sequence data this is encouraging, although as we have already discussed, not necessarily conclusive.
This could be achieved by using a combination of both high fidelity phi29 DNA polymerase at the experimental side and appropriate sequencing data analysis at the computational side.
Another example is the connection between original experimental data such as sequencing data, additional data such as genomic references or gene annotations used when analysing the data, and results of such analyses such as lists of genetic variants or gene expression levels.
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