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Even when phenotypic differences are large between natural or domesticated strains, the underlying genetic basis is often complex, and causal genomic regions need to be identified by quantitative trait locus (QTL) mapping.
In summary, our data demonstrate that a large number of protein changes during the lung cancer disease process can be identified by quantitative proteomic approaches.
Even here, with subregional dissection into the frontal, temporal, and occipital cortex, we are still incorporating heterogeneous layers and nuclei, which means that significant, small changes imply much larger focal effects that are likely to be identified by quantitative morphology.
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Mupirocin was identified by quantitative structure property relationship models as a good candidate for remote liposomal loading.
Appropriate formulation, considering the sensory attributes, was identified by Quantitative Descriptive Analysis (QDA) and used for studying rheological parameters.
Genomic regions related to the high-temperature growth of S. cerevisiae were identified by quantitative trait locus (QTL) mapping (Steinmetz et al. [2000]; Sinha et al. [2006], [2008]).
Changes in the expression pattern of messenger ribonucleic acid for matrix metalloproteinases (MMP), tissue inhibitor of metalloproteinases (TIMP), and pro-apoptotic (p53 and Bax) and anti-apoptotic (Bcl-2) proteins were identified by quantitative polymerase chain reaction.
Two viruses were identified by quantitative PCR.
The expression level of microRNA-210 was identified by quantitative real-time PCR analysis.
Differentially methylated regions (DMRs) were identified by quantitative differentially methylated regions (QDMR) [ 31].
Hepatocellular, pancreatic and gastric cancer cell lines expressing CD133 were identified by quantitative FACS (Table 2).
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