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Several methods and many pipelines are proposed to analyse sequences from small RNA deep-sequencing data sets to see if they meet a given set of rules [ 31, 32].
Data are presented as mean ± s.e.m.; unpaired t-test: n.s., not significant at 95% confidence level (e) Normalized expression of miR-29 star sequences from small RNA sequencing reads.
Using R software we calculated the expected distribution of sequences from small size samples compared to a larger reference dataset.
We obtained over half a billion sequences from small RNA libraries (Table 1).
As part of a search for NIRVs in NCBI databases we found strong BLAST matches of NP sequences from filoviruses to translated genomic sequences from small mammals.
Conserved E. electricus miRNA orthologs were identified by BLASTN comparison of expressed sequences from small RNA libraries to sequences from the Rfam database [ 54].
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As non-high-throughput divisions still can contain submissions with several thousand sequences, we filtered this set to retain sequences from small-scale analyses only and therefore removed articles that submitted more than 100 sequences.
To circumvent cloning bias issues, we next tested the ability of pyrosequencing technology [33] to (a) generate genome sequence from small amounts of phage DNA, and (b) allow de novo assembly of whole phage genomes.
This should prove useful for high throughput sequencing from small or rare samples of cells, or from DNA enrichment techniques that are particularly low-yielding.
We anticipate that sequencing from small quantities of input DNA (<1 ng) will become a significant aid to genetic and genomic studies of P. falciparum in the field, particularly when combined with effective methods for removal of host DNA contamination.
Additional file 1: Size distribution of sequences obtained from small RNA sequencing of Atlantic cod early developmental stages and four juvenile tissues.
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