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We attempt to introduce the latest developments in drug design based on computational techniques, including protein structure modeling, docking, binding site prediction, quantitative structure activity relationship (QSAR), and molecular dynamics simulation.
However, this pattern is lost when annotations are made purely based on computational techniques and the functions are conserved with almost equal probabilities irrespective of the sequence conservation.
This depicts the difference in the quality of these two annotations, and indicates that many annotations based on computational techniques may be incorrect.
Functional conservation measures from GO annotations based on computational techniques such as electronic annotation based on sequence similarity has a behavioral pattern completely different from Figures 3, 4 and 5.
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We focus on PCO2 since our previous studies based on computational intelligence (CI) techniques have shown that 43 mmHg PCO2 is an important threshold for predicting PVL.
First, a 3D steady-state detailed model is produced based on computational fluid dynamics (CFD) techniques.
This paper describes a methodology based on computational and analytical modelling techniques in the prediction of building internal pressure gain functions.
Some criteria for design of the most critical parts of the cooling system are provided using both a model based on Computational Fluid Dynamics (CFD) techniques and the analytical thermal model.
On the other hand, models based on Computational Fluid Dynamics (CFD) techniques have proven to be useful in simulating fluid flow in hydrocyclones, and in predicting the separation efficiency of solid particles in the separator for a wide range of operating and design conditions.
An integrated methodology, based on Computational fluid Dynamics (CFD) techniques and the dimensionless buoyancy flux number, F/U3L, a parameter that can be associated with the flow characteristics, taking advantage of the dynamic similarity of the flow domain, is presented and used for the simulation of the plume dispersion.
We focus on algorithmic techniques based on computational geometry that have been developed for shape matching, simplification, and morphing.
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