Complex Network Characterization Using Graph Theory and Fractal Geometry: The Case Study of Lung Cancer DNA Sequences
| Autor: | Jurij Mihelič, Matej Babič, Michele Calì |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
fractal dimension
Network complexity Theoretical computer science Computer science Quantitative Biology::Tissues and Organs Physics::Medical Physics Characterization (mathematics) lcsh:Technology Fractal dimension lcsh:Chemistry 03 medical and health sciences 0302 clinical medicine Fractal General Materials Science natural sciences lcsh:QH301-705.5 Instrumentation 030304 developmental biology DNA geometry Complex networks Topological properties Bioengineering Fluid Flow and Transfer Processes 0303 health sciences bioengineering lcsh:T Process Chemistry and Technology General Engineering Graph theory complex networks Complex network respiratory system lcsh:QC1-999 Computer Science Applications lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 030220 oncology & carcinogenesis Embedding lcsh:Engineering (General). Civil engineering (General) topological properties lcsh:Physics circulatory and respiratory physiology |
| Zdroj: | Applied Sciences Volume 10 Issue 9 Applied Sciences, Vol 10, Iss 3037, p 3037 (2020) |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app10093037 |
| Popis: | This paper discusses an approach developed for exploiting the local elementary movements of evolution to study complex networks in terms of shared common embedding and, consequently, shared fractal properties. This approach can be useful for the analysis of lung cancer DNA sequences and their properties by using the concepts of graph theory and fractal geometry. The proposed method advances a renewed consideration of network complexity both on local and global scales. Several researchers have illustrated the advantages of fractal mathematics, as well as its applicability to lung cancer research. Nevertheless, many researchers and clinicians continue to be unaware of its potential. Therefore, this paper aims to examine the underlying assumptions of fractals and analyze the fractal dimension and related measurements for possible application to complex networks and, especially, to the lung cancer network. The strict relationship between the lung cancer network properties and the fractal dimension is proved. Results show that the fractal dimension decreases in the lung cancer network while the topological properties of the network increase in the lung cancer network. Finally, statistical and topological significance between the complexity of the network and lung cancer network is shown. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|