Sentence examples for multiple unrelated genes from inspiring English sources

Our results show how a single oncoprotein-directed pathway can silence multiple, unrelated genes.

The present study validates the approach of using a short dsRNA molecule specifically designed with a single guide strand to suppress the expression of multiple unrelated genes implicated in a particular medical condition.

Whereas, if both gene G2 and protein P2 are ANNOTATED TO the same biological function B2, it does not imply that gene G2 should ENCODE protein P2, given the possible multiple cardinality of annotation of unrelated genes and proteins to the same biological function.

Our experiment shows that mutating genes in multiple, unrelated biochemical networks can produce evolutionary novelty and reveals that identifying adaptive mutations is often insufficient to explain the mechanism of these new phenotypes.

Even in the absence of restricted gene flow, multiple unrelated founding events could also shape the same pattern of population genetic structure [ 4].

Perhaps these populations contain genes not segregating in the IBM RILs that confer large effects to multiple traits; alternatively, the large-effect QTL overlapping for multiple unrelated traits could be caused by distinct genes (underlying multiple QTL) located very close together.

The present study demonstrates proof of concept for the design of artificial short RNAs with at least partial complementarity to multiple unrelated transcripts, and which suppress the expression of the corresponding unrelated genes.

We will refer to the above-described procedure for searching for a disease gene by exome sequencing in multiple unrelated patients as the 'intersection' approach.

Here we demonstrate using individual cancer datasets that global expression patterns can be divided into biologically meaningful clusters defining tumour cell and stromal elements, and also that many of these gene signatures are conserved across multiple unrelated human cancer datasets.

Types of peptides range from those that uniquely identify a specific protein isoform from a single gene, to those that arise from multiple unrelated proteins and therefore provide little protein/gene information.

Obviously, a filtering approach that focuses on genes that are affected by variants in which multiple unrelated patients harbor potential disease-causing mutations (Hoischen et al., 2010) is unsuitable.