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Manuscript Submission Deadline 31 March 2023

The concurrent rise of single-cell omics technologies and computational modelling has enabled the exploration of biological phenomena at an unprecedented resolution. Consequently, there is a substantial amount of effort dedicated to single-cell omics for exploring gene expression dynamics, tissue heterogeneity and disease pathogenesis. However, a large proportion of single-cell omics-focused studies describe cell populations present in the system with incomplete projection of the underlying biological mechanisms at play. There is an unmet need for systematic extrapolation of the information gained with single-cell technologies into tissue, organ and organismal scales that can provide mechanistic insights of disease pathogenesis and elucidate future translational path to either emulate proposed treatment or identify control points that can be perturbed towards disease treatment. While we have seen successful application of single-cell omics in development of rare cell population-based cancer therapies, this approach would benefit greatly from methodologies that can be ubiquitously adapted to other systems and disease areas. This will require co-evolution of data analysis methods, new research and computational modelling to establish a mechanistic foundation and gain insights into tissue and/or organ level biology.

This research topic invites work on current and future strategies on single-cell omics data analysis and/or computational modeling, focused towards addressing the challenges of gaining mechanistic tissue and/or organ level insights into diseases that can inform future studies, potentially culminating in novel therapies.

The areas covered in this Research Topic include but not limited to:

- Methods that integrate available omics datasets- computational modeling and omics analysis that incorporate tissue and/or organ environment to gain mechanistic insights of disease states.

- Original research articles that lay a mechanistic foundation by means of analyzing and interpreting omics data.

- Computational modelling that relies on single-cell omics data and incorporates biophysical environment of cells/tissue to understand and predict tissue and organ dynamics.

- Review articles that discuss current progress in these areas.

Keywords: Single-cell, Omics, Mechanistic Modeling, Systems Biology, Tissue, Organ, Multiscale


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

The concurrent rise of single-cell omics technologies and computational modelling has enabled the exploration of biological phenomena at an unprecedented resolution. Consequently, there is a substantial amount of effort dedicated to single-cell omics for exploring gene expression dynamics, tissue heterogeneity and disease pathogenesis. However, a large proportion of single-cell omics-focused studies describe cell populations present in the system with incomplete projection of the underlying biological mechanisms at play. There is an unmet need for systematic extrapolation of the information gained with single-cell technologies into tissue, organ and organismal scales that can provide mechanistic insights of disease pathogenesis and elucidate future translational path to either emulate proposed treatment or identify control points that can be perturbed towards disease treatment. While we have seen successful application of single-cell omics in development of rare cell population-based cancer therapies, this approach would benefit greatly from methodologies that can be ubiquitously adapted to other systems and disease areas. This will require co-evolution of data analysis methods, new research and computational modelling to establish a mechanistic foundation and gain insights into tissue and/or organ level biology.

This research topic invites work on current and future strategies on single-cell omics data analysis and/or computational modeling, focused towards addressing the challenges of gaining mechanistic tissue and/or organ level insights into diseases that can inform future studies, potentially culminating in novel therapies.

The areas covered in this Research Topic include but not limited to:

- Methods that integrate available omics datasets- computational modeling and omics analysis that incorporate tissue and/or organ environment to gain mechanistic insights of disease states.

- Original research articles that lay a mechanistic foundation by means of analyzing and interpreting omics data.

- Computational modelling that relies on single-cell omics data and incorporates biophysical environment of cells/tissue to understand and predict tissue and organ dynamics.

- Review articles that discuss current progress in these areas.

Keywords: Single-cell, Omics, Mechanistic Modeling, Systems Biology, Tissue, Organ, Multiscale


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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