title: A graph spectral analysis of the structural similarity network of protein chains.
abstract: We present a simple method for the analysis of large networks based on their graph spectral properties. One of the advantages of this method is that it uses a single numerical computation to identify subclusters in a connected graph, which can significantly simplify the complexity involved in analyzing large graphs. This is illustrated using a network of protein chains constructed on the basis of their structural similarities. The large-scale network properties and the cluster and subcluster organization of the protein chain network are presented. We summarize the results of structural and functional analyses of the nodes present in these clusters and elucidate the implications of structural similarity in the protein chain universe.
authors.affiliation: Molecular Biophysics Unit, Indian Institute of Science, Bangalore, India.
authors.forename: O
authors.initials: O
authors.lastname: Krishnadev
authors.forename: K V
authors.initials: KV
authors.lastname: Brinda
authors.forename: Saraswathi
authors.initials: S
authors.lastname: Vishveshwara
mesh_terms: D016000:Cluster Analysis; D030562:Databases, Protein; D008958:Models, Molecular; D011485:Protein Binding; D017510:Protein Folding; D020836:Protein Structure, Quaternary; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D040681:Structural Homology, Protein
chemical_list: D011506:Proteins