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The network-based methodologies can efficiently integrate the biological information with the computational techniques and link the disease-related genes to relevant proteins and disease types.
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The proposed methodology can efficiently and effectively aid in the design of an economically feasible Net Zero Energy vaccine warehouse for the developing world.
The methodology can efficiently design for very small transponder-related blocking probability (e.g., <10−4) by using simple, straightforward simulation and analysis techniques.
Such an obstacle can be overcome by obtaining knowledge on the initially unknown PU spectrum allocation and consequently, our methodology can efficiently contribute to this direction.
It is shown that with careful substream power assignments this transmission methodology can efficiently utilize the capacity of rank-deficient channels as it can approach the capacity limits of the multiple antenna channel closely over the entire range of available signal-to-noise ratios and system sizes.
Such a requirement makes the optimization problem difficult to solve, and has kept the researchers busy towards devising methodologies, which can efficiently handle the problem.
which focuses on dealing with information technologies and computational methodologies that can efficiently and accurately manipulate –omics data and transform molecular information into biological knowledge.
It is concluded that the proposed methodology can be efficiently used to optimize inflow control valve design in cases in which computational resources and available time are limited.
The results presented in the paper showed that the proposed methodology can be efficiently used in the integrated study of history matching and uncertainty analysis, providing a practical way to increase the reliability of prediction through reservoir simulation models reducing the uncertainty through observed data.
Now that genotyping technologies and methodologies are in place, novel methods that can efficiently assemble large genetic epidemiology cohorts without having to re-create longitudinal prospective cohorts are required.
We chose to simulate crosstalk reactions using both methodologies because while classical deterministic modeling based on differential equations can efficiently simulate simple systems, their assumptions of spatial and temporal homogeneity are not always accurate in dynamic biological systems.
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