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In other words, Bai et al. were able to 'purify' their sample in silico.
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GC-TRFLP was then performed on these samples in silico and the resulting data used to estimate community SAD (Table 4).
Since about 86% of reads sampled in silico from PstI or BsrFI restriction sites could be aligned uniquely to the genome, it appears that 13%to29%9% of sites were not sampled by RAD library preparation.
We detected five TE families that were overrepresented in our empirical data, with 11- to > 100-fold differences in TE hits relative to reads sampled in silico from the B73 reference genome.
One hundred and thousand reads with an average length of 269 bases were sampled in silico using the 454 setting from 19 microbial genomes, 3 viruses and human chromosomes 8 and 21 (Supplementary Table 1).
To ascertain that species misassignment and potential biases in read loss does not cause S expression values to lose accuracy, we mixed pairs of human and mouse samples in silico and compared expression values before and after mixing the samples and using S (Fig. 1e, f), with good correlation.
This downregulation was also seen in an independent and large sample series, curated by the In Silico Transcriptomics (IST) database, where DCLK1 was found to be significantly more expressed in the normal samples (n = 64) compared with the cancer samples (n = 991; P = 1.00E-05).
We identified candidate subsets of genes (by their ontologic category or contribution to sample variation in silico) that might underwrite the transcriptomic resemblance of human muscle to mouse soleus.
CETS model predictions of bulk DNA neuronal proportions excluded neuronal and non-neuronal DNA methylation profiles of the same sample for in silico matrix generation as per standard bootstrapping techniques.
Case control samples for in silico replication in stage 3 were taken from several published type 2 diabetes GWAS in East Asian individuals.
In other words, the distribution of modularity arising in our samples of in silico metabolic networks can provide a null hypothesis to evaluate whether a biological network shows unusual modularity.
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