Abstract
Many complex systems such as biological and social systems can be modeled using graph structures called biological networks and social networks. Instead of studying separately each of the elements composing such complex systems, it is easier to study the networks representing the interactions between the elements of these systems. A commonly known fact in biological and social networks’ analysis is that in most networks some important or influential elements (e.g. essential proteins in PPI networks) are placed in some particular positions in a network. These positions (i.e. vertices) have some particular structural properties. Centrality measures quantify such facts from different points of view. Based on centrality measures the graph elements such as vertices and edges can be ranked from different points of view. Top ranked elements in the graph are supposed to play an important role in the network. This paper presents a comprehensive review of existing different centrality measures and their applications in some biological networks such as Protein-Protein interaction network, residue interaction and gene–gene interaction networks.
Keywords: Centrality measures, graph structures, network analysis, network structures.
Current Bioinformatics
Title:Centrality Measures in Biological Networks
Volume: 9 Issue: 4
Author(s): Mahdieh Ghasemi, Hossein Seidkhani, Faezeh Tamimi, Maseud Rahgozar and Ali Masoudi-Nejad
Affiliation:
Keywords: Centrality measures, graph structures, network analysis, network structures.
Abstract: Many complex systems such as biological and social systems can be modeled using graph structures called biological networks and social networks. Instead of studying separately each of the elements composing such complex systems, it is easier to study the networks representing the interactions between the elements of these systems. A commonly known fact in biological and social networks’ analysis is that in most networks some important or influential elements (e.g. essential proteins in PPI networks) are placed in some particular positions in a network. These positions (i.e. vertices) have some particular structural properties. Centrality measures quantify such facts from different points of view. Based on centrality measures the graph elements such as vertices and edges can be ranked from different points of view. Top ranked elements in the graph are supposed to play an important role in the network. This paper presents a comprehensive review of existing different centrality measures and their applications in some biological networks such as Protein-Protein interaction network, residue interaction and gene–gene interaction networks.
Export Options
About this article
Cite this article as:
Ghasemi Mahdieh, Seidkhani Hossein, Tamimi Faezeh, Rahgozar Maseud and Masoudi-Nejad Ali, Centrality Measures in Biological Networks, Current Bioinformatics 2014; 9 (4) . https://dx.doi.org/10.2174/15748936113086660013
DOI https://dx.doi.org/10.2174/15748936113086660013 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
Related Articles
-
Acute Antithrombotic Treatment of Ischemic Stroke
Current Vascular Pharmacology Berberine: A Plant-derived Alkaloid with Therapeutic Potential to Combat Alzheimer’s disease
Central Nervous System Agents in Medicinal Chemistry The Coronary Circulation in Arterial Hypertension
Immunology, Endocrine & Metabolic Agents in Medicinal Chemistry (Discontinued) Indoxyl Sulfate: A Candidate Target for the Prevention and Treatment of Cardiovascular Disease in Chronic Kidney Disease
Current Drug Targets Physiological and Pharmacological Regulation of Hepatic 3-Hydroxy-3- Methylglutaryl Coenzyme A Reductase
Current Medicinal Chemistry - Immunology, Endocrine & Metabolic Agents Editorial from Editor-in-Chief [‘Chronic Obstructive Pulmonary Disease: Economical Burden and Quality of Life in 2008”]
Current Respiratory Medicine Reviews Matrix Metalloproteinases as Potential Targets in the Venous Dilation Associated with Varicose Veins
Current Drug Targets Preconception Care for Diabetic Women: Background, Barriers, and Strategies for Effective Implementation
Current Diabetes Reviews <i>Uncaria rhynchophylla</i> and its Major Constituents on Central Nervous System: A Review on Their Pharmacological Actions
Current Vascular Pharmacology Nimodipine Reappraised: An Old Drug With a Future
Current Neuropharmacology Cyclooxygenase Inhibitors: Instrumental Drugs to Understand Cardiovascular Homeostasis and Arterial Thrombosis
Cardiovascular & Hematological Disorders-Drug Targets Regulators of Platelet cAMP Levels: Clinical and Therapeutic Implications
Current Medicinal Chemistry Neurodegeneration and Neuroinflammation in Diabetic Retinopathy: Potential Approaches to Delay Neuronal Loss
Current Neuropharmacology Pharmacological Implications of MMP-9 Inhibition by ACE Inhibitors
Current Medicinal Chemistry Prophylactic Potential of Conventional and Supercritical Garlic Extracts to Alleviate Diet Related Malfunctions
Recent Patents on Food, Nutrition & Agriculture Telomeres and their Role in Aging and Longevity
Current Vascular Pharmacology Hyperglycaemia and Vitamin D: A Systematic Overview
Current Diabetes Reviews Emerging Therapeutic Approaches Multi-Targeting Receptor Tyrosine Kinases and G Protein-Coupled Receptors in Cardiovascular Disease
Cardiovascular & Hematological Agents in Medicinal Chemistry Combinational Approaches Targeting Neurodegeneration, Oxidative Stress, and Inflammation in the Treatment of Diabetic Retinopathy
Current Drug Targets Inhibitors of 11β-Hydroxylase (CYP11B1) for Treating Diseases Related to Excess Cortisol
Current Medicinal Chemistry