Sentence examples for implications of sequence from inspiring English sources

Using the highly diverse pspC locus, we have now characterized the functional and immune implications of sequence diversity within the PspC protein.

Consequently, the implications of sequence conservation in a less well-studied lineage are often unpredictable and require further lineage-specific investigation.

To gain insight into the implications of sequencing error in phylogenomic applications, we performed a series of simple, descriptive analyses.

To explore the implications of sequencing information and stated preferences for return of results among research participants.

We also provide evidence that each FFRP has significantly functionally diverged at the protein sequence level, and in subsequent sections we will explore the implications of this sequence level divergence on the function of each FFRP.> -wrap-foot> Upper triangle contains pairwise coefficient of functional divergence (θij) between FFRP i and j and the standard error (SE).

Overall, the results of our studies provide insights into the functional implications of protein sequence diversity and the role of variant-specific immunity in its maintenance.

The evolutionary and biotechnological implications of these sequences are discussed.

Amid all these interesting implications of genome sequencing, the debate concerning the correct use of scientific terminology remains.

The full implications of massive sequencing in a clinical setting have been discussed extensively [ 7- 10], including discussion of some of the economic considerations, which are of considerable general interest [ 11].

To estimate the biological implications of the sequencing data in silico, we applied four different software tools that allow for the prediction of the deleteriousness on protein function of each somatic mutation and found ∼75% of the mutations classified as harmful by all four algorithms.

The large number of reads allowed an in-depth analysis of errors, and we found that PCR-induced errors composed the vast majority of non-organism derived species variants, an observation that has significant implications for sequence clustering of similar high-throughput data.