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Automatic analysis of poses using self-organizing maps (AuPosSOM) 19 represents a new approach that uses the concept of contact fingerprint similarity for virtual screening.
Automatic analysis of poses using self-organizing maps (AuPosSOM) represents an alternative approach for the evaluation of docking results based on the clustering of compounds by the similarity of their contacts with the receptor.
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This section explains the model and the constraints defined in it as the basis of the analysis of posed problems as the product of problem posing.
We delimit our discussion to the collection and analysis of posed questions, with an objective of investigating how much exploration-based learning took place.
In this research, we have conducted analysis of posed problems in elementary school students' problem posing activity with Monsakun in order to understand whether Monsakun encourages them to think about the structure of arithmetic word problems.
A detailed analysis of pose prediction and virtual screening results in dependence of the number of protein structures considered in the conformational ensemble will be presented and limitations of the approach will be highlighted.
In this paper, we report on our analysis of posed problems by elementary school students on Monsakun in terms of whether Monsakun encourages learners to think about the structure of arithmetic word problems.
In this paper, we propose a method for recognition of human actions by analysis of skeleton poses.
First, a mathematical model is proposed for the analysis of dynamic poses under different input frequencies.
The methodology of economic analysis of law poses a more significant challenge to traditional accounts of law.
The fingerprint is atom based since this allows for an exact and easily interpretable analysis of docking poses.
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