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This demonstrates that CSP based approaches can provide an accurate way in which to predict protein/ligand complex structure using in silico NMR approaches.
While in situ and GUS reporter based approaches can provide high spatial resolution, they require sacrificing the sampled tissue and thus cannot be used to easily monitor gene expression dynamics in individual plants over time.
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As shown in previous studies [37], [38], [39] a systematic model based approach can provide biological insight and information to the experimentalist.
Model-based approaches can provide useful support in addressing this new challenge.
Diagram-based approaches can provide an important avenue to help us think about, and plan for, complex systems (Tversky 2011; Kessell and Tversky 2009; Huggins and Jones 2012).
These solution-based approaches can provide a basis for large-area inorganic nanoparticle-based electric devices through the design of bio-nanomaterials at the molecular level.
Although global array-based approaches can provide high resolution data on CNVs in individuals, these methods are limited by low throughput, high cost, and a long turnaround time, and there remains a need for simple, cost-efficient methods to screen chromosomal alterations across larger populations.
Compared to traditional regression approaches, network-based approaches can provide a holistic picture that captures the complexity of intracellular and intercellular interactions in diseases [ 21].
There has been increasing recognition that network-based approaches can provide insight into critical cellular elements that help define phenotypic state.
The proposed SVDD-based approach can provide a suitable mechanism to map component evaluation grades to failure risks based on the probabilistic behaviors of power system failures.
In this paper, we investigate how a software component based approach can be used to provide a reusable and adaptable architecture for executing HPC tasks on accelerator-based clusters.
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