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These methods will greatly facilitate the generation of more full genome PRRSV sequences globally.
Thus, the ability to isolate the PSD, particularly when combined with proteomic methods, will greatly aid our understanding of neuropsychiatric illnesses.
These two methods will greatly improve single-cell analyses of fission yeast by flow cytometry and thereby allow a much more detailed, exact and sophisticated cell-cycle analysis.
These methods will greatly advance genome assembly and annotation of multigene families in non-model species.
A combination of these methods will greatly accelerate the recruitment of natural resistance gene biodiversity for crop improvement.
Our methods will greatly contribute to the isolation of high performance mAbs needed for sensitive diagnostics and therapeutic purposes.
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Application of this method will greatly enhance the flexibility of PLC-based motion control system and extend its application range.
We suggest that the automated method will greatly facilitate further progress in the use of AFM for the determination of receptor and multi-protein architecture.
In the long term, it is envisaged that the method will greatly increase the accuracy and efficiency of SPH methods, while retaining the flexibility of SPH in modelling free surface and multiphase flows.
In this research, we consider that the error saturation (ES) condition, which is caused by the use of gradient descent method, will greatly slow down the learning speed of BP algorithm.
However, with face alignment on the database, it is believed that the proposed method will greatly outperform all methods reported so far in the literature.
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