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However, expression levels of key responding genes of the microarray need to be validated by real-time PCR.
However, expression levels of key genes responding on the microarray need to be validated [ 2].
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However, for the potential of this high throughput technology to be realised in pain research, microarrays need to be combined with other technologies.
Undeniably, the results obtained using microarrays need to be validated with other techniques (for example in situ hybridization and immunohistochemistry should permit a better definition of specific cell types implicated in differences in gene expression).
The large amount of information obtained with high-throughput technologies like expression microarrays needs to be processed in order to be comprehensible to molecular biologists.
Perren Cobb Washington University in St . LouisChakraborty adds that microarray platforms need to accommodate sample degradation too.
It is well known that data from microarray analysis need to be interpreted cautiously (Kothapalli et al, 2002).
Data from microarray analysis need to be interpreted cautiously and therefore, we provide guidelines for making cross-platform correlations.
At the same time, lists of inflammation-specific genes identified during microarray experiments need to be incorporated into biological models that describe their molecular interactions.
Despite the attractive features identified above, prospective users of statistical outlier labeling in microarray contexts need to be cautious in their application of these methods.
To obtain significant results, microarray data need to undergo statistical processing to differentiate between signal changes caused by direct experimental factors and arising from the indirect experimental factors such as specific methods used, as well as from inaccuracies of the measurements.
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