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This report describes the implementation of MeDiChI - originally developed by David Reiss to evaluate ChIP-chip profiles [ 15] – for the analysis of datasets generated by massive parallel sequencing.
Using cancer as an example, Phil Stevens (Sanger Centre) presented data on characterizing structural variation by massive parallel sequencing technology to identify structural rearrangements in cancer cell lines using genome-wide screening approaches.
Our proposed workflow to screen for mutations in the BRCA1 and BRCA2 genes consists first in the use of the BRCA1 and BRCA2 homopolymer assay (BRCA HP) followed by massive parallel sequencing with the 454 GS Junior sequencer and using the BRCA MASTR amplicon kit to generate the patient libraries.
Cells were then subjected to chromatin immunoprecipitation (ChIP) followed by massive parallel sequencing (ChIP-seq).
These enhancers were identified by massive parallel sequencing of P300 bound regions (ChIP-Seq).
In contrast, when the expression profiles generated by massive parallel sequencing from Tang's data set was compared with their qPCR results, 36% of measurements of differential expression were false positive and 49% of the genes measured as differentially expressed by qPCR were not detected by sequencing (Figure 4C).
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This estimate is in agreement with a previous study that assessed somatic mutations in FFPE material by using semiconductor-based massive parallel sequencing [ 18].
Transcriptome analyses by means of a massive parallel sequencing technology, RNA-Seq, circumvents the above-mentioned limitations [ 11, 12], it is highly replicable [ 13] and therefore a very attractive research method for an unbiased identification of differentially expressed genes.
We therefore used the massive parallel sequencing technology by mRNA-Seq to elucidate the rice transcriptome under stress due to –P and ++P in order to provide a comprehensive overview of the primary molecular events resulting from phosphate stress.
Pooled massive parallel sequencing followed by individual genotyping in a large cross sectional cohort has allowed identification of the common SNPs around the IL28B gene which best predicted response to PegIFN/R for the treatment of hepatitis C. We argue that prediction of failure to respond to therapy is the most useful parameter for clinical management.
Current 454-pyrosequencing technology enables massive parallel sequencing.
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