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The interpretation of microarray data remains a major challenge because of the complexity of the underlying biological networks.
Although the use of microarray technology has seen exponential growth, analysis of microarray data remains a challenge to many investigators.
Constructing an accurate predictive model for clinical decision-making on the basis of a relatively small number of tumor samples with high-dimensional microarray data remains a very challenging problem.
Although microarray technology has become common and affordable, analysis and interpretation of microarray data remains challenging.
However, the validity of individual microarray data remains low compared to data generated by means of RT-PCR, Northern-Blot, Western-Blot, RFLP, or even DNA Sequencing.
Inferring a regulatory network from DNA microarray data remains a great challenge despite the fact that numerous computational methods have been published [ 33- 39].
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Although there are known non-biological variations present in microarray data, it remains unquestionable that array technology will have a great impact on aquatic toxicology.
However, ERAP1 transcript was not noticed in the microarray data, thus it remains to be determined whether ERAP1 is functional in osteoblast proliferation and differentiation.
Yet even where microarray studies have been conducted, their data remains only nominally accessible to those with sufficient means, experience and time to extract useful information.
Thus, the precise role of PAR2 activation in proliferation at least in HEK293 cells remains obscure based on microarray data alone.
microarray data reproduced, but some concerns remain.
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