Author: Rinku Sharma

Publisher: Frontiers Media SA

Published: 2023-08-25

Total Pages: 121

ISBN-13: 2832531679

The biological complexity essentially includes and involves processes that are mediated through explicitly non-linear interactions that are often typically entangled in nature. These comprise a myriad of interactions among a vast number of entities such as genes, proteins, metabolites, and species, widely varying in scale. These interactions render biological systems across spatial and temporal scales as complex adaptive systems having features like: self-organisation, modularity, emergence, non-linear interactions, collective response and adaptation. The theory of complex networks offers an appropriate formal framework for modelling such complex systems. The enormous wealth of biological data generated by high-throughput techniques, as also through empirical investigations can be analysed using the aforementioned formal framework to obtain important insights into biological complexity.The concept of networks can be used:1) to explore the relationships between entities resulting in network generation; 2) to guide the analytic procedure based on existing network(s) as prior knowledge; and 3) to analyze the prior network(s) regarding their topology and attributes. Complex networks, being ubiquitous, permeate the biological systems across spatial and temporal scales. The objective of this collection is to highlight some very salient features of such inherent complexity in biological systems by adopting a network theoretic perspective. The anticipated pay-off is obtaining a deeper insight explicitly into the systems-level interactions and the emergent complex behaviour of the systems. Also, investigating the propulsive forces which lend various networks with akin topological characteristics that would help to merge vivid information related to various molecular interactions into a single framework, thereby permitting a structural perspective of the cellular dynamics.The application may include – exploring the disease/environmental stress response and trait mechanism using different omics platforms, candidate gene discovery and validation, network-guided discovery and deployment of omics approaches in biology; modern genetic improvement methods for delivering genes in addition to high throughput and precise phenotyping methodologies, exploring the disease/environmental stress response mechanism, marker re-prioritization, network-guided biomarker discovery etc.