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Clustering is a method that identifies or classifies drugs based on their structural backbone or scaffolds.
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The classification of these polysaccharides has been based on their structural units: namely, the backbone of CS is composed of repeating disaccharide units of N-acetyl d-galactosamine (GalNAc) and d-glucuronic acid (GlcUA), while DS consists of GalNAc and l-iduronic acid (IdoUA) instead of GlcUA.
A similar effect can be achieved by apriori filtering of candidate model structures based on their structural properties.
In addition, both polysaccharide fractions (EPS-1 and EPS-2) from crude EPS were mainly composed of (2 → 6 -linked β-d-fructofuranosyl residues backbone with (2 → 1)-linked branches based on their structural characterization by FT-IR spectroscopy, methylation analysis and 13C NMR spectroscopy.
It is hypothesized that proteins are not only subject to selective pressure based on their structural properties, but also their local dynamic properties.
It means the training set members are firstly grouped together based on their structural similarity.
Madden et al. (2006) hypothesized that NPs differentially bind metal ions based on their structural configuration.
Kinases were recently classified in three major groups based on their structural properties [1].
Fish AFPs are classified into antifreeze glycoproteins (AFGPs) and type I to IV AFPs based on their structural diversity [2].
This classifier was then used to predict the status of the test participant based on their structural scan alone.
In total, there are 21,684 interfaces collected in Prism, which are clustered into 3,799 clusters based on their structural similarity.
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