A Review on Applications of Graph Theory in Network Analysis of Biological Processes

2014 ◽  
Vol 6 (1) ◽  
pp. 27-43
Author(s):  
Elmira Mohyedinbonab ◽  
Mo Jamshidi ◽  
Yu-Fang Jin
Keyword(s):  
Graph Theory ◽  
Network Analysis ◽  
Biological Processes

scholarly journals Application of graph theory in diagnosis of malocclusion

2017 ◽  
Vol 7 (1) ◽  
pp. 126-134
Author(s):  
LALITHA P
Keyword(s):  
Graph Theory ◽  
Network Analysis ◽  
Treatment Planning ◽  
Graphical Model ◽  
Statistical Technique ◽  
Diagnosis And Treatment ◽  
Biological Processes ◽  
Statistical Tool ◽  
New Approach ◽  
Graphic Model

The objective of this article is to use graph theory as a modality to simplify and explain the properties of complex biological processes in orthodontics so as to aid in diagnosis and treatment planning. Network analysis, an innovative statistical tool, provides a new approach to understand complex problems. It is a graphical model that encodes probabilistic relationship among variables of interest. When used incombination with statistical technique this graphic model which illustrates the causal relationship among different variables and hence can be used to gain understanding about a problem and predict the consequences of intervention. Orthodontics deals with correction of malocclusion and other dentofacial anomalies which usually have a complex multifactorial etiology. Diagnosis and treatment planning may need the correlation of the clinical, radiographic, and the functional data. The use of graph theory to analyse these datas can drastically reduce the complexity of the pertaining problem. The topology of the dentofacial system obtained by network analysis could allow orthodontists to visually evaluate and anticipate the co-occurrence of auxological anomalies during individual craniofacial growth and possibly localize reactive sites for a therapeutic approach to malocclusion. This article discusses the scope of graph theory and its use in dentistry in general and orthodontics in particular.

scholarly journals Carcinogenesis and Chemotherapy Viewed from the Perspective of Stoichiometric Network Analysis (SNA): What Can the Biological System of the Elements Contribute to an Understanding of Tumour Induction by Elemental Chemical Noxae (e.g., Ni2+, Cd2+) and to an Understanding of Chemotherapy?

2003 ◽  
Vol 3 ◽  
pp. 319-341 ◽  
Author(s):  
Stefan Franzle ◽  
Bernd Markert
Keyword(s):  
Network Analysis ◽  
Biological System ◽  
Cell Biology ◽  
Essential Feature ◽  
Comprehensive Treatment ◽  
Biological Processes ◽  
Tumour Induction ◽  
Stoichiometric Network Analysis ◽  
Autocatalytic Networks

The biological application of stoichiometric network analysis (SNA) permits an understanding of tumour induction, carcinogenesis, and chemotherapy. Starting from the Biological System of the Elements, which provides a comprehensive treatment of the functions and distributions of chemical (trace) elements in biology, an attempt is made to interrelate the essential feature of biology and — regrettably — of tumour genesis by superimposing SNA reasoning on common features of all crucial biological processes. For this purpose, aspects, effects and drawbacks of autocatalysis (identical reproduction which can occur either under control or without control [in tumours]) are linked with the known facts about element distributions in living beings and about interference of metals with tumours (in terms of both chemotherapy and carcinogenesis). The essential role of autocatalysis in biology and the drawbacks of either controlled or spontaneous cell division can be used to understand crucial aspects of carcinogenesis and chemotherapy because SNA describes and predicts effects of autocatalysis, including phase effects that may be due to some kind of intervention. The SNA-based classifications of autocatalytic networks in cell biology are outlined here to identify new approaches to chemotherapy.

scholarly journals Group Measures and Modeling for Social Networks

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Vincent Levorato
Keyword(s):  
Complex System ◽  
Social Networks ◽  
Graph Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Network Modeling ◽  
Complex Interactions ◽  
Social Network Modeling

Social network modeling is generally based on graph theory, which allows for study of dynamics and emerging phenomena. However, in terms of neighborhood, the graphs are not necessarily adapted to represent complex interactions, and the neighborhood of a group of vertices can be inferred from the neighborhoods of each vertex composing that group. In our study, we consider that a group has to be considered as a complex system where emerging phenomena can appear. In this paper, a formalism is proposed to resolve this problematic by modeling groups in social networks using pretopology as a generalization of the graph theory. After giving some definitions and examples of modeling, we show how some measures used in social network analysis (degree, betweenness, and closeness) can be also generalized to consider a group as a whole entity.

scholarly journals Graph theory-based network analysis of regional uncertainties of the US Economy

2020 ◽  
Vol 540 ◽  
pp. 123064 ◽  
Author(s):  
Rangan Gupta ◽  
Chi-Keung (Marco) Lau ◽  
Xin Sheng
Keyword(s):  
Graph Theory ◽  
Network Analysis ◽  
Us Economy ◽  
The Us

An investigation into colour combination in paintings via graph theory

2019 ◽  
Vol 8 (4) ◽  
Author(s):  
Samaneh Jolany Vangah ◽  
Yousef Jamali ◽  
Mozaffar Jamali
Keyword(s):  
Image Processing ◽  
Graph Theory ◽  
Network Analysis ◽  
Visual Arts ◽  
Digital Image ◽  
Degree Distribution ◽  
Network Science ◽  
Node Centrality ◽  
Classification Of Images

Abstract In visual arts, painting is deeply reliant on the colour combination for its impact, depth and emotion. Recently, many studies have focused on image processing, regarding identification and classification of images, using some colour features such as saturation, hue, luminance and so forth. This study aims to delve into some of the painting styles from the perspective of graph theory and network science. We compared a number of famous paintings to find out the likely pattern that an artist uses for colour combination and juxtaposition. To achieve this aim, the digital image of a painting is converted to a graph where each vertex represents one of the painting’s colours. In this graph, two vertices would be adjacent if and only if the two relative colours could be found in at least two adjacent pixels in the digital image. Among the several tools for network analysis, clustering, node centrality and degree distribution are used. Outcomes showed that artists unconsciously are following subtle mathematical rules to reach harmony and coordination in their work.

scholarly journals Identifying novel genes and biological processes relevant to the development of cancer therapy-induced mucositis: An informative gene network analysis

PLoS ONE ◽  
2017 ◽  
Vol 12 (7) ◽  
pp. e0180396 ◽  
Author(s):  
Cielito C. Reyes-Gibby ◽  
Stephanie C. Melkonian ◽  
Jian Wang ◽  
Robert K. Yu ◽  
Samuel A. Shelburne ◽  
...  
Keyword(s):  
Network Analysis ◽  
Cancer Therapy ◽  
Gene Network ◽  
Biological Processes ◽  
Informative Gene ◽  
Novel Genes ◽  
Gene Network Analysis

A network analysis of miRNA mediated gene regulation of rice: crosstalk among biological processes

2015 ◽  
Vol 11 (8) ◽  
pp. 2273-2280 ◽  
Author(s):  
Chittabrata Mal ◽  
Arindam Deb ◽  
Md. Aftabuddin ◽  
Sudip Kundu
Keyword(s):  
Gene Regulation ◽  
Network Analysis ◽  
Target Genes ◽  
Functional Network ◽  
Biological Processes

Modules of miRNAs' co-targeting and co-functional network of rice identify miRNAs co-regulating target genes having several interrelated biological processes.

Sign in / Sign up

Export Citation Format

Share Document