TSAR, a new graph-theoretical approach to computational modeling of protein side-chain flexibility: Modeling of ionization properties of proteins

2011 ◽  
Vol 79 (9) ◽  
pp. 2693-2710 ◽  
Author(s):  
Oleg V. Stroganov ◽  
Fedor N. Novikov ◽  
Alexey A. Zeifman ◽  
Viktor S. Stroylov ◽  
Ghermes G. Chilov
Keyword(s):  
Computational Modeling ◽  
Theoretical Approach ◽  
Side Chain ◽  
Chain Flexibility ◽  
Graph Theoretical Approach

Polypeptides Folding: Rules for the Calculation of the Backbone Dihedral Angles φ starting from the Amino Acid Sequence

2020 ◽  
Author(s):  
Michele Larocca
Keyword(s):  
Amino Acid ◽  
Amino Acid Sequence ◽  
Theoretical Approach ◽  
Polypeptide Chain ◽  
Hydrophobic Effect ◽  
Side Chain ◽  
Dihedral Angles ◽  
Mechanical Forces ◽  
Specific Chemical

<p>Protein folding is strictly related to the determination of the backbone dihedral angles and depends on the information contained in the amino acid sequence as well as on the hydrophobic effect. To date, the type of information embedded in the amino acid sequence has not yet been revealed. The present study deals with these problematics and aims to furnish a possible explanation of the information contained in the amino acid sequence, showing and reporting rules to calculate the backbone dihedral angles φ. The study is based on the development of mechanical forces once specific chemical interactions are established among the side chain of the residues in a polypeptide chain. It aims to furnish a theoretical approach to predict backbone dihedral angles which, in the future, may be applied to computational developments focused on the prediction of polypeptide structures.</p>

A Spectral Graph Theoretical Approach to Oriented Energy Features

2017 ◽  
Vol 31 (01) ◽  
pp. 1755001 ◽  
Author(s):  
Güleser Kalaycı Demir
Keyword(s):  
Theoretical Approach ◽  
Graph Laplacian ◽  
Texture Segmentation ◽  
Contour Detection ◽  
Feature Extraction Method ◽  
Spectral Graph ◽  
Graph Theoretical Approach ◽  
Novel Method ◽  
Oriented Energy ◽  
Complex Valued

In this work, we propose a novel method for determining oriented energy features of an image. Oriented energy features, useful for many machine vision applications like contour detection, texture segmentation and motion analysis, are determined from the filters whose outputs are enhanced at the edges of the image at a given orientation. We use the eigenvectors and eigenvalues of graph Laplacian for determining the oriented energy features of an image. Our method is based on spectral graph theoretical approach in which a graph is assigned complex-valued edge weights whose phases encode orientation information. These edge weights give rise to a complex-valued Hermitian Laplacian whose spectrum enables us to extract oriented energy features of the image. We perform a set of numerical experiments to determine the efficiency and characteristics of the proposed method. In addition, we apply our feature extraction method to texture segmentation problem. We do this in comparison with other known methods, and show that our method performs better for various test textures.

Mutually unbiased bases: a group and graph theoretical approach

2018 ◽  
Vol 94 (1) ◽  
pp. 014007 ◽  
Author(s):  
Gernot Alber ◽  
Christopher Charnes
Keyword(s):  
Theoretical Approach ◽  
Mutually Unbiased Bases ◽  
Graph Theoretical Approach
Sign in / Sign up

Export Citation Format

Share Document