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A plausible mechanism proposed recently is that bacterial genomes have different Polymerase III mutator genes that may introduce GC-biased mutations depending on the alpha subunit isoforms [ 59].
When the buffering effect is mediated through those conserved Hsp90-dependent hubs, it allows organisms to reveal the effect of different mutations depending on their genetic backgrounds or environmental challenges.
The distribution of minor SNPs exclusively within haplotypes coding for reduced COMT activity may suggest different evolutionary models (e.g., enrichment for functional compensatory mutations or positive selection leading to carrying of neutral mutations) depending on the functional contribution of these SNPs.
In general, in the context of multi-drug treatments, we classify all possible mutations into three classes, singly-, doubly-, and triply-resistant mutations, depending on how many different drugs (out of the three drugs in the combination) they confer resistance to.
The data demonstrate a differential effect of the mutations depending on both their nature and their location.
Different risk estimates for BRCA mutations, depending on the type of population studied, also attest to this point.
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The impact of replication-dependent mutations depends on the deleterious mutation rate U, for which only indirect estimates are available (see " Methods").
The consequences of mutations depend on the environment.
The phenotypic effects of random mutations depend on both the architecture of the genome and the gene trait relationships.
Whether or not the activating effects of these mutations depend on S1 cleavage has not yet been examined.
It is accepted that the phenotypic consequences of these somatic mutations depend on the type of cells involved, the nature of the initial mutation and its timing.
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