In our research, we opted for a colored voxel representation due to both its fast computation and accuracy.
Taking both computation time and accuracy into account, using BEAGLE for pre-phasing and IMPUTE2 for imputation would be a good strategy for large scale imputation of whole genome sequence markers.
The proposed approach is extensively evaluated with three state-of-the-art approaches on both synthetic and real datasets, and our approach outperforms the other approaches in terms of both computation time and accuracy.
The objective of this work is to compare the performance of different optimization algorithms for both computation time and accuracy criteria.
This makes the difference between both search method in computation and accuracy very small.
Existing measurement techniques lack a multi-objective network measurement mechanism to overcome various overheads, like communication cost, controller computation, and accuracy in a real-time environment.
The diversity of models and implementations reflects the various requirements for the balance between time complexity of the computation and accuracy of the results.
While the method has been shown to provide computation and accuracy advantages, it is challenging to apply to domains with complex geometry.
Through combining a steady state model with a transient state model, both the computation efficiency and accuracy are ensured.
Note that a bad choice of free fluxes or their associated values can result in poor algorithmic performance (both in computation time and accuracy).
