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We emphasize the necessity to develop more fine grained methods for selecting services not only based on their abstract functional properties (and non-functional attributes, as, e.g., done in [16]) but also based on their functionality when executed.
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The description of chemical structures as a collection of connected molecular fragments is a basic requirement of coarse grained simulation methods like molecular fragment dynamics.
In order to balance between performance and energy consumption, fine-grained methods, such as process-level power management, were proposed.
Along this chapter, we will review these coarse-grained methods, and explain their physical foundations and their range of applicability.
The presented atomistic and coarse-grained methods offer a natural framework to their conceptualization in polynary systems, entangled or crosslinked homo- or heteropolymers.
Precise modeling of this behavior requires fully atomistic methods in and around the extended defect, but the flow of point defects entering the defect region can be treated by coarse-grained methods.
The CMAP maintains the simplicity of other course-grained methods, including Boolean networks, but there are essential differences.
Because of the difficulty of NMR studies and timescale problems in all-atom MD, coarse-grained methods have emerged as an inexpensive and powerful alternative.
Coarse-grained methods or any sort of accelerated MD could be a way to take benefit of simulation in a near future.
The analysis is performed at the Cα level so that ensembles from one-bead coarse-grained methods are also suitable input.
The design of coarse-grained methods successfully applied for large timescale investigations of protein dynamics encompasses entirely different modeling strategies (Emperador et al., 2008; Jamroz et al., 2013b; Maisuradze et al., 2010).
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