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Thus, we propose that peptide microarray methodologies are a powerful new tool for elucidating molecular interactions at chromatin.
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The resolution of this microarray methodology is ∼15% in exon inclusion differences [15].
Microarray methodology was developed as an epochal method to simultaneously analyze enormous data sets for gene expression patterns in various biological conditions [ 7].
It is critical that the findings of microarray screening methodologies are validated to produce scientifically robust results, using the most sensitive and reproducible method of gene expression quantitation, reverse transcription quantitative PCR (RT-qPCR) [ 16].
Several power calculations for microarray methodologies exist, consequently sample size was determined and compared with two power calculation approaches.
Originally, these techniques were employed in conjunction with microarray platforms; however, high-throughput sequencing methodologies are now routinely being used.
The methodologies are illustrated on two data sets; the first are the microarray gene expressions measured by two plat- forms; the Affymetrix and the Amersham.
The MVs replacement in microarrays data is a recent research field and numerous new and innovative methodologies are developed.
While the above mentioned list of the potential pitfalls in microarray and qPCR methodologies is long, most sources of error can be controlled through robust experimental designs, good laboratory practices, and rigorous normalization of the data.
For the first time the microarray methodology has been applied for the simultaneous identification of different mixed population of spoilage yeast and bacteria directly isolated from wine, thus indicating the practicability of oligonucleotide microarrays as a contamination control in wine industry.
This three-color microarray methodology can be utilized for pre-hybridization quality assessment [ 18], to facilitate automated post-hybridization image analysis [ 24], as well as post-hybridization data filtering [ 19].
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