Computational analysis of carbohydrate recognition based on hybrid QM/MM modeling: a case study of norovirus capsid protein in complex with Lewis antigen

2018 ◽  
Vol 20 (7) ◽  
pp. 4652-4665 ◽  
Author(s):  
Toyokazu Ishida

Computational modeling of carbohydrate recognition in norovirus capsid protein.

2019 ◽  
Vol 211 ◽  
pp. 137-160
Author(s):  
Jean Yeh ◽  
Goong Chen ◽  
Cong Gu ◽  
James “Tom” Thurman ◽  
Alexey Sergeev ◽  
...  

Author(s):  
B. Addison ◽  
N. Sarigul-Klijn ◽  
R. Roberto ◽  
A. Jamali ◽  
M. Thompson

This paper presents a high fidelity computational approach to be used in validation of biomechanics experimental measurements. As a demonstration, a case study involving a spinous process implant to correct scoliosis is presented. The biomechanical behavior of the spinous process and implant under tensile loading is investigated using experiments and computations. The experimental study examined the ultimate strength of calf thoracic and lumbar spinous processes in three pullout directions. A statistical analysis was performed on the experimental results to reveal relationships and variations between pullout direction and vertebral type. The finite element high fidelity computational analysis was performed to validate the experimental results. In the process, the material properties of cortical and trabecular bone were elucidated for calf spinous processes. Good comparisons are obtained. The high fidelity computational approach detailed here should serve useful in validation of experimental values from spine biomechanics experimental.


2019 ◽  
Vol 18 (3) ◽  
pp. 1019-1031 ◽  
Author(s):  
Sean Peters ◽  
Peter G. Hains ◽  
Natasha Lucas ◽  
Phillip J. Robinson ◽  
Brett Tully

2019 ◽  
Vol 6 (7) ◽  
pp. 190139 ◽  
Author(s):  
T. Morita ◽  
H. Koda

A pervasive belief with regard to the differences between human language and animal vocal sequences ( song ) is that they belong to different classes of computational complexity, with animal song belonging to regular languages, whereas human language is superregular. This argument, however, lacks empirical evidence since superregular analyses of animal song are understudied. The goal of this paper is to perform a superregular analysis of animal song, using data from gibbons as a case study, and demonstrate that a superregular analysis can be effectively used with non-human data. A key finding is that a superregular analysis does not increase explanatory power but rather provides for compact analysis: fewer grammatical rules are necessary once superregularity is allowed. This pattern is analogous to a previous computational analysis of human language, and accordingly, the null hypothesis, that human language and animal song are governed by the same type of grammatical systems, cannot be rejected.


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