Skoči na glavni sadržaj

Pregledni rad

https://doi.org/https://doi.org/10.47960/2232-9080.2026.31.16.25

AN ILLUSTRATIVE OVERVIEW OF THE SYNERGY BETWEEN GRAPH THEORY AND PEPTIDE ANALYSIS USING COMBINATORIAL OPTIMIZATION

Anton Vrdoljak orcid id orcid.org/0000-0002-0559-0981 ; Sveučilište u Mostaru, Fakultet građevinarstva, arhitekture i geodezije *

* Dopisni autor.


Puni tekst: hrvatski pdf 1.119 Kb

str. 23-32

preuzimanja: 0

citiraj

Puni tekst: engleski pdf 1.146 Kb

str. 25-34

preuzimanja: 0

citiraj


Sažetak

Many contemporary problems in biomedicine, biophysics, and bioinformatics, as well as in numerous other fields of engineering and social sciences, can be reduced to mathematical modeling based on graph theory. Mathematical modeling is generally interpreted as the act of representing a real-world system through mathematical formulations and equations, aiming to develop and implement a model that facilitates subsequent analysis, design, and system optimization. The aim of this paper is to demonstrate, through an illustrative account of the synergy between graph theory and peptide analysis, how combinatorial optimization enables the resolution of complex biophysical problems in a computationally elegant and efficient manner. Due to their importance in analyzing and predicting peptide properties, the proposed model focuses on constructing a smaller yet representative subset of amino acid scales. To this end, a Variable Neighborhood Search (VNS) approach is employed – a contemporary metaheuristic in the field of combinatorial optimization.

Ključne riječi

graph theory; dominating set; amino-acid scales; combinatorial optimization; variable neighborhood search

Hrčak ID:

348071

URI

https://hrcak.srce.hr/348071

Datum izdavanja:

18.6.2026.

Podaci na drugim jezicima: hrvatski

Posjeta: 0 *