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Both technical aspects of performing genomewide microarray or next generation sequencing analysis on single cells and interpretation issues are subject of debate.
The size of gene sets queried can range from the tens (e.g., the results of qPCR experiments) to hundreds or even thousands (e.g., the gene signature results from microarray or next generation sequencing experiments).
Therefore, a given gene can yield multiple expression values through microarray or next generation RNA sequencing (RNA-Seq) analyses.
Biochemical network models have thus long served effectively as platforms for analysis of high-throughput experimental data, e.g., microarray or next generation sequencing based gene expression data [ 3– 5].
Inferring gene regulatory networks (GRNs) from experimental data is a challenging task becoming increasingly important with routine practical use of corresponding experimental techniques, such as RNA interference combined with microarray or next generation sequencing.
Mutant analysis in combination with microarray or next generation sequencing provides a powerful approach for discovering fiber developmental mechanisms by comparing gene expression in mutant vs. wild-type plants [ 11, 13– 15].
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Before analyzing the DNA of a single cell by microarray or next-generation sequencing, a whole-genome amplification (WGA) process is required, but it substantially distorts the frequency and composition of the cell's alleles.
This strategy could be of great benefit for labs with limited funds or limited access to microarray or next-generation sequencing facilities.
When used in combination with microarray or next-generation sequencing technologies, dDIP will allow researchers to map genome-wide DNA strand breaks as well as other types of DNA damage and to establish a clear profiling of altered genes and/or intergenic sequences in various experimental conditions.
A signature of miR species is amenable to rapid quantification by reverse transcriptase-PCR, whereas a global profile can be quantified by microarray or next-generation sequencing platforms.
Summary: Pattern Gene Finder (PaGeFinder) is a web-based server for on-line detection of gene expression patterns from serial transcriptomic data generated by high-throughput technologies like microarray or next-generation sequencing.
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