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.
This special issue welcomes the submission of reviews, mini reviews, methods, opinions, and original research manuscripts aiming to address the role of network theoretic approach in deciphering the nature of complex biological networks related to following major areas:
• Sustainable agricultural practices: The studies related to impact of climate change on plants growth and development at molecular level; elucidating multiple environmental stress signaling and molecular response in plants; identification of potential targets for tolerant variety development and plant-microbe interaction; discovery and deployment of target genomic regions and QTLs/genes for genetic improvement using modern approaches including genomic selection, GWAS and genome editing tools; advanced sequencing and genotyping tools/platforms for different omics platform; establishing connections between different layers of genome biology through multiple omics platform including 3D and Hi-C technologies.
• Biomedical research: Prioritize disease-causing genes, identification of disease-associated sub-networks and capturing therapeutic responses, Network-assisted analysis (NAA) of GWAS (genome-wide association analysis) data and understanding the trait development through regulatory network analysis.
• Biodiversity conservation: The studies related to identification of key populations shaping the structure and connectivity of meta-population systems using molecular markers/ microsatellite data. Deployment of different omics platform in understanding and characterizing the germplasm diversity, conservation and usage.
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.
This special issue welcomes the submission of reviews, mini reviews, methods, opinions, and original research manuscripts aiming to address the role of network theoretic approach in deciphering the nature of complex biological networks related to following major areas:
• Sustainable agricultural practices: The studies related to impact of climate change on plants growth and development at molecular level; elucidating multiple environmental stress signaling and molecular response in plants; identification of potential targets for tolerant variety development and plant-microbe interaction; discovery and deployment of target genomic regions and QTLs/genes for genetic improvement using modern approaches including genomic selection, GWAS and genome editing tools; advanced sequencing and genotyping tools/platforms for different omics platform; establishing connections between different layers of genome biology through multiple omics platform including 3D and Hi-C technologies.
• Biomedical research: Prioritize disease-causing genes, identification of disease-associated sub-networks and capturing therapeutic responses, Network-assisted analysis (NAA) of GWAS (genome-wide association analysis) data and understanding the trait development through regulatory network analysis.
• Biodiversity conservation: The studies related to identification of key populations shaping the structure and connectivity of meta-population systems using molecular markers/ microsatellite data. Deployment of different omics platform in understanding and characterizing the germplasm diversity, conservation and usage.
