Network science-based approaches are increasingly used to build more powerful tools to better understand functional relationships in microbiome studies. Application of co-occurrence networks have begun to provide evidence to support the role of keystone species in moderating health and disease as well as allowed for studies of community structure that more accurately reflect community function. In addition, network approaches have led to a more complete integration of ‘omics data to more robustly investigate systems biology. There is currently a critical need to provide context for these approaches through biological experimentation to determine how these tools can advance ever growing ‘omics sciences.
In recent years, the complexity of microbiome and other multidimensional datasets have been well addressed, including features of compositionality and sparsity. Recent reviews have highlighted the use of networks based approaches to study intra-community interactions and functional relationships, form predictive models using Bayesian inference-based approaches, and integrate multi-omics data in systems biology studies.
The goal of this Research Topic is to highlight these emerging approaches and provide a context for their use that will increase their rigor and accessibility. Through reports of carefully planned and replicated experiments, measures of network features like modularity and centrality can be placed in a biological context to understand their practical application to ‘omics datasets. Further, these tools can be used to achieve better integration of multi-omics datasets to deliver on the promises of systems biology that, to date, have been limited by data complexity and lack of appropriate methods to more simple correlative analyses.
This Research Topic invites manuscript submissions addressing, but not limited to, the following themes:
• Development of new tools for network construction, analysis, and integration of ‘omics data
• Application of network science-based themes to biological and environmental studies to assess features of community ecology
• Integrative systems biology studies of microbial systems using multi-omics data
• Use of Bayesian networks and machine learning to elucidate mechanistic dynamics
• Evaluation of reproducible themes or patterns in community structure using network-based approaches
Network science-based approaches are increasingly used to build more powerful tools to better understand functional relationships in microbiome studies. Application of co-occurrence networks have begun to provide evidence to support the role of keystone species in moderating health and disease as well as allowed for studies of community structure that more accurately reflect community function. In addition, network approaches have led to a more complete integration of ‘omics data to more robustly investigate systems biology. There is currently a critical need to provide context for these approaches through biological experimentation to determine how these tools can advance ever growing ‘omics sciences.
In recent years, the complexity of microbiome and other multidimensional datasets have been well addressed, including features of compositionality and sparsity. Recent reviews have highlighted the use of networks based approaches to study intra-community interactions and functional relationships, form predictive models using Bayesian inference-based approaches, and integrate multi-omics data in systems biology studies.
The goal of this Research Topic is to highlight these emerging approaches and provide a context for their use that will increase their rigor and accessibility. Through reports of carefully planned and replicated experiments, measures of network features like modularity and centrality can be placed in a biological context to understand their practical application to ‘omics datasets. Further, these tools can be used to achieve better integration of multi-omics datasets to deliver on the promises of systems biology that, to date, have been limited by data complexity and lack of appropriate methods to more simple correlative analyses.
This Research Topic invites manuscript submissions addressing, but not limited to, the following themes:
• Development of new tools for network construction, analysis, and integration of ‘omics data
• Application of network science-based themes to biological and environmental studies to assess features of community ecology
• Integrative systems biology studies of microbial systems using multi-omics data
• Use of Bayesian networks and machine learning to elucidate mechanistic dynamics
• Evaluation of reproducible themes or patterns in community structure using network-based approaches
