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However, verifying this would require much deeper EST sampling and a methodologically consistent approach for profiling transcripts (e.g. microarrays).
In the present study we used label-free quantitative proteomics approach for profiling the proteome of resected cancer and autologous normal kidney tissues.
In this work, we described a new interesting approach for profiling circulating miRNAs in plasma samples using a chip-based platform, the QuantStudio 3D digital PCR.
RNA degradome sequencing that integrates a modified 5′-rapid amplification of cDNA ends protocol with next-generation sequencing technologies is a high-throughput approach for profiling the 5′-end of uncapped RNA fragments on a genome-wide scale.
Though in general the DASL-based approach is more reliable than the IVT-based approach for profiling degraded mRNA samples, our MDMR analyses suggest that RNA degradation and other factors still play important roles in determining dataset variance, thereby potentially confounding differential expression analyses.
Accordingly, the combination of computational prediction and microarray analysis may be a feasible and practical approach for profiling studies of both known and predicted small RNAs.
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Semeraro et al. [74] uses a different approach for profile construction.
Our specific correlation approach for profile analysis may therefore be adapted to peak shift determination in usual spectral or angular RWGs based detection techniques [ 2– 4, 7].
Common approaches for profiling patients and phenotyping disorders may include the following tools: checklists, questionnaires, interviews, physical examinations, imaging, laboratory tests, and psychological/psychiatric evaluations.
The goals of this study were to use proteomic mass spectrometry approaches for profiling, fractionation, and identification of serum proteins from breast cancer patients for discovery of new biomarkers of stage and nodal status.
However, similar approaches for profiling PKMT activity on a proteome-wide scale have not been described.
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