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Although identifying genomic subsets of mutated genes may inform therapeutic options, a systematic survey of tumor mutational spectra is required to improve our understanding of the underlying mechanisms of mutagenesis involved in cancer etiology.
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This information is useful for the identification of the genomic subset of CTCF sites that might contribute to differential cell- and stage-specific expression due to their sensitivity to cytosine methylation, potentially mediating changes in large-scale chromatin organization during development and disease.
Genotyping-by-sequencing (GBS), which is one of the most important methods for detecting SNPs, is a genome-reduction technique based on the high-throughput next-generation sequencing of genomic subsets targeted by restriction enzymes15,16.
This procedure, which can be generalized to any species at a low per-sample cost, is based on high-throughput, next-generation sequencing of genomic subsets targeted by restriction enzymes (REs).
However, we still see a number of proteins in any genomic subset with a substantial number of unique epitopes (even by the relaxed JanusMatrix evaluation that allows variation in the MHC-facing residues).
A genomic subset GS is the union of non-overlapping intervals GS j of size L(GS j ) along the human genome.
Whole-exome sequencing combined with RNA sequencing of IMPC allowed us to identify somatic mutations in genes involved in polarity, DNAH9 and FMN2 (8% and 2%, respectively) or ciliogenesis, BBS12 and BBS9 (2% each) or genes coding for endoplasmic reticulum protein, HSP90B1 and SPTLC3 (2% each) and cytoskeleton, UBR4 and PTPN21 (2% each), regardless of the genomic subset.
The BPRs constitute a particular genomic subset defined by intervals B i of size L(B i ).
Genomic analyses of subsets of this sequentially accrued patient population were reported previously [ 9, 14, 15].
There are many questions in bacterial biology, however, which can be adequately addressed with population genomic approaches that employ subsets of the genome [ 44], such as MLST, rMLST and cgMLST; and for these analyses NGS datasets provide a rich source of information [ 15].
The main challenges lie in the visualization and interpretation of genomic relationships, and the redefinition of microbial taxonomy when subsets of genomic data are so evidently in conflict with one another, and with the "canonical" molecular taxonomy.
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