Sentence examples for mutations from which from inspiring English sources

Daughter cells that inherit these wrong bases carry mutations from which the original DNA sequence is unrecoverable (except in the rare case of a back mutation, for example, through gene conversion).

Interestingly, our simulation of mutations produces the seemingly opposing result that timing robustness is not itself robust to mutations – from which we conclude that it is a property that must be actively maintained by evolution.

If we approximate these expressions by the highest order term (i.e. the most rapidly growing exponential), representing the pool of cells with C−1 oncogenic mutations from which the new malignant lineages are drawn by one more mutation, we obtain several results (Supplementary Tables S1 and S2 and Figure 2).

Recently, this unveiled phenomenon showed the interdependency and biologic modularity of somatic mutations from which oncogenicity emerges [ 27, 28] rather than the old paradigm of one single point mutation to trigger an oncogenic phenotype.

Similarly, a propagator ratio g > 1 signals an increase in substitution probability of nonsynonymous over synonymous mutations, from which we infer that at least a fraction (g − 1)/ g of the nonsynonymous changes are beneficial (McDonald and Kreitman 1991; Smith and Eyre-Walker 2002).

These effects are likely indirect, resulting from accelerated mutation rates, from which advantageous mutations can arise and lead to a more aggressive phenotype.

The mutation spectrum itself is a 4D-matrix with the layout (Sample, Prefix, Suffix, Mutation Type ), from which the typical signatures of acting mutational processes can be extracted via non-negative matrix factorization using e. g. the R package NMF (Gaujoux and Seoighe, 2010).

We do not assume that we know which of the S copies hold the mutation or from which of the original copies (maternal or paternal) the mutation is descended.

The selection pressure can be calculated on different levels, from a single gene to the whole mutation dataset, from which candidate driver genes can be predicted and the number of driver mutations can be estimated.

In the companion paper to this one (Nik-Zainal et al., 2012), we show that many breast cancer genomes have distinctive mutation processes, from which a nonnegative matrix factorization algorithm identified five separate signatures.

In contrast to Bravo-San Pedro (and similar to the data in this study), Sanchez-Danes et al. did not observe an alteration in basal autophagy in the G2019S mutation fibroblasts from which the pluripotent cells they used in their study were derived.