Modularity in Biological Networks
Network modeling, from the ecological to the molecular scale has become an essential tool for studying the structure, dynamics and complex behavior of living systems. Graph representations of the relationships between biological components open up a wide variety of methods for discovering the mechan...
Saved in:
Published in | Frontiers in genetics Vol. 12; p. 701331 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Frontiers Media S.A
14.09.2021
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Summary: | Network modeling, from the ecological to the molecular scale has become an essential tool for studying the structure, dynamics and complex behavior of living systems. Graph representations of the relationships between biological components open up a wide variety of methods for discovering the mechanistic and functional properties of biological systems. Many biological networks are organized into a modular structure, so methods to discover such modules are essential if we are to understand the biological system as a whole. However, most of the methods used in biology to this end, have a limited applicability, as they are very specific to the system they were developed for. Conversely, from the statistical physics and network science perspective, graph modularity has been theoretically studied and several methods of a very general nature have been developed. It is our perspective that in particular for the modularity detection problem, biology and theoretical physics/network science are less connected than they should. The central goal of this review is to provide the necessary background and present the most applicable and pertinent methods for community detection in a way that motivates their further usage in biological research. |
---|---|
Bibliography: | ObjectType-Article-2 SourceType-Scholarly Journals-1 ObjectType-Feature-3 content type line 23 ObjectType-Review-1 Reviewed by: Dario Ghersi, University of Nebraska Omaha, United States; Vinícius Vieira, Universidade Federal de São João del-Rei, Brazil This article was submitted to Computational Genomics, a section of the journal Frontiers in Genetics Edited by: Marco Pellegrini, Institute of Computer Science and Telematics, Italian National Research Council, Italy |
ISSN: | 1664-8021 1664-8021 |
DOI: | 10.3389/fgene.2021.701331 |