ライフサイエンスコーパス: coarse-graining

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1 of network visualization, data ordering and coarse-graining.

2 ple and applicable to models at any level of coarse-graining.

3 that of a macromolecule for the criteria of coarse-graining a cytoplasmic model.

4 for network visualization, data ordering and coarse-graining accomplished this goal.

5 e any additional adjustable parameters after coarse graining and is computationally very fast.

6 The storage errors due to coarse-graining and diffusion trade off so that informat

7 based multiscale simulations where a dynamic coarse-graining and force-blending method is required.

8 cussed, with a key focus on structure factor coarse-graining and hydration contribution.

9 the theoretical underpinnings and history of coarse-graining and summarize the state of the field, or

10 bonding contact metric which is an intuitive coarse graining approach.

11 the development of the model, two levels of coarse-graining are explored and the importance of retai

12 Using coarse-graining as an analysis method reveals that cofil

13 ions of molecular states to provide powerful coarse-graining capabilities, for example to merge Boole

14 matic methodology, called essential dynamics coarse-graining (ED-CG), has been developed for defining

15 ematic methodology called essential dynamics coarse-graining (ED-CG).

16 olids and nonperturbative approach (by super-coarse-graining elasticity into internal bending modes)

17 Systematic coarse-graining from an all-atom description of the disa

18 Because of its large size, coarse graining helps to simplify and to aid in the unde

19 In this study, we used a combination of coarse graining, hierarchical natural move Monte Carlo a

20 Although coarse-graining is employed in MD and other approaches,

21 Extension Algorithm via Covariance Hessian) coarse-graining method, in which the force constants of

22 Here, a coarse-graining method, REACH, is introduced, in which t

23 Efficient coarse-graining methods are required to reduce the intra

24 So far, exact and heuristic coarse-graining methods have been mostly restricted to t

25 oying a combination of experimental data and coarse-graining methods, are used to explore the structu

26 challenge, multiscale approaches, including coarse-graining methods, become necessary.

27 Coarse graining of protein interactions provides a means

28 lly combining the Morone-Makse algorithm and coarse graining of the network in which we regard a comm

29 This relationship was robust to scaling and coarse graining of the sensor array.

30 Coarse-graining of atomistic force fields allows us to i

31 Coarse-graining of protein interactions provides a means

32 It has been recently shown that the coarse-graining of the structures of polypeptide chains

33 r the first time, a long-standing problem in coarse-graining polymer systems, namely, how to accurate

34 to improve model elaboration, refinement and coarse graining procedures to better understand the rele

35 n modeling large regions of the cortex, many coarse-graining procedures have been invoked to obtain e

36 function of shear strain, and use that in a coarse-graining rate equation formulation for constructi

37 acids and lipid molecules); 3), shape-based coarse-graining (resolving overall protein and membrane

38 l-atom molecular dynamics; 2), residue-based coarse-graining (resolving single amino acids and lipid

39 These "coarse-graining" studies have addressed observed as well

40 applying our molecular renormalization group coarse-graining technique to double-stranded DNA, we sol

41 To analyze it we construct an exact coarse graining that reduces the model to a Markov proce

42 By coarse-graining the spoken word testimony into synonym s

43 tarting model and approximations inherent in coarse graining, these results are consistent with exper

44 in difficulties by applying a gradient-based coarse graining to RNA-ligand systems and solving the pr

45 twork model, which invoke similar degrees of coarse-graining to the dynamics but use different potent

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