Mapping the Structural Landscape of Protein Families with Geometric Feature Vectors

Pattern recognition encompasses two fundamental tasks: description and classification. Given an object to analyze, a pattern recognition system first generates a description of it (i.e., the pattern) and then classifies the object based on that description (i.e., the recognition). Two general approaches for implementing pattern recognition systems, statistical and structural, employ different t...

When considering the prediction of a structural class for a protein as a classification problem, usually a classifier is based on a feature vector x ∈ R, where the features represent certain attributes of the primary sequence or derived properties (e.g., the predicted secondary structure) of a given protein. Since the structure of a protein (i.e., its native conformation) is stable only under s...

The death domain superfamily, comprising the death domain, death effector domain, caspase recruitment domain and pyrin domain subfamilies, is one of the largest classes of protein interaction modules, and plays a particularly critical function in the assembly and activation of apoptotic and inflammatory complexes. Members of the death domain superfamily share a common structural feature, the 6-...

Protein structure prediction is critical to functional annotation of the massively accumulated biological sequences, which prompts an imperative need for the development of high-throughput technologies. As a first and key step in protein structure prediction, protein structural class prediction becomes an increasingly challenging task. Amongst most homological-based approaches, the accuracies o...

This paper describes an approach to automated identi cation of three-dimensional (3D) common structural features of proteins. The structure of a protein was represented by a set of secondary structure elements (SSEs) in the same manner used in our previous work, where only -helices and -strands were considered. The maximal common subgraph matching algorithm, based on a graph theoretical clique ...

This paper describes an approach to automated identification of three-dimensional common structural features of proteins. The structure of a protein was represented by a set of secondary structure elements (SSEs) in the same manner used in our previous work, where only α-helix and β-strand secondary structure elements were considered. The maximal common subgraph algorithm, based on a graph theo...

Reliable damage detection is one of the most critical tasks in composite plate structures. Ultrasonic guided waves are acknowledged as an effective way of structural health mo...

magnesium oxide nanoclusters have attracted much attention due to their potential applications to catalysis and novel optoelectronic materials. in the present study, we have studied the electronic and magnetic properties of the stoichiometric magnesium oxide nanoclusters (mgo)n  for n = 2-20. although the binding energy increases with the size of the cluster, it  reaches the asymptotic limit of...

in this paper, the performance of 11 different distances for image retrieval and classification, based on color, shape and texture, is evaluated. the precision-recall measure and the correct classification rate of the k-nn classifier are used to evaluate retrieval and classification performances, respectively. the experimental results for a database of 1000 images from 10 different semantic gro...