Sentence examples for performance of proteins from inspiring English sources
Aside from an overview of the fundamentals of ultrasound, including a cursory outline of ultrasonic cavitation, heat generation and acoustic energy determination via calorimetry, examples of ultrasound treatment for improvements in the dissolution, hydration, hydrophobicity, emulsifying and rheological performance of proteins are described.
We also compared performance of proteins found to be secreted by ovarian cancer cells but were either not identified in mouse plasma or not found to be elevated in plasma from tumor bearing mice.
In a similar manner, we produced a fusion protein between the negative-control antibody single-chain Fv(HyHEL10) [ 44] and IL-10, to assess the therapeutic performance of proteins with comparable clearance rates but different targeting selectivity.
Theoretical models have been studied to investigate the major driving forces to achieve the most optimal performance of protein adsorption.
Further, compared to the conventional preprocessing, the use of morphological analysis as preprocessing improves the performance of protein name recognition and reduces the execution time.
Therefore, it is necessary to develop reliable and effective computational approaches to further improve the performance of protein subcellular prediction and, at the same time, cover more species.
Expanded bed adsorption (EBA) is a special chromatography technique with perfect classification of adsorbent particles in the column, thus the performance of protein adsorption in expanded beds is particular, obviously nonuniform and complex along the column.
The robustness of this general purification strategy was evaluated by examining the performance of protein produced in five different refolding batches derived from the same E. coli culture experiment.
The performance of protein structures extracted from MD simulations in virtual screening has been assessed.
We believe this framework provides useful insights into the performance of protein function prediction tools.
In this paper, we study the performance of protein sequence classification using SLFNs.
