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Methods for parallel simulation of solid state NMR powder spectra are presented for both shared and distributed memory parallel supercomputers.
Meanwhile, there are established methods for parallel implementation of L2 regression model, which can be applied to our approach to efficiently process a large number of noisy images.
To improve the speed and ensure the precision of simulation at the same time, coupling methods for parallel running RELAPSim codes were proposed in this study.
The establishment of rapid cloning, expression and protein detection procedures has therefore become a major field of interest for the design of high-throughput methods for parallel expression of proteins in multiple expression systems.
DNA microarray technologies are among the most frequently used methods for parallel global analysis of gene expression.
This finding highlights the need for developing efficient methods for parallel analysis of gene overexpression phenotypes in diverse conditions.
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The development and implementation of a new method for parallel dynamic load balancing is presented.
An event-driven method for parallel simulation of a class dynamic Monte Carlo models is presented.
We developed a method for parallel SBVS following the MR approach, which enables the screening of large molecular libraries on public cloud resources or on commodity hardware clusters.
Computation time can also be accelerated with compute unified device architecture (CUDA) implementation because we designed the proposed method for parallel processing.
We developed a method for parallel expression and purification of recombinant proteins with a hexahistidine tag (His-tag) or glutathione S-transferase (GST -tag from bacterial expression systems.
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