Data-driven modelling of biological networks dramatically improved our understanding on the mechanistic casualties of various intra- and inter-cellular behaviour of living systems. For example, systems-level models of cellular signaling networks like in healthy and diseased brain cells or cancer tumors will continue to be highly valuable tools allowing incorporation of sufficient biological details and exhibit physiological validity to serve as explanatory tools. Similarly, data-driven models comparing aberration of regulatory pathways in healthy and diseased states can provide valuable mechanistic insights into novel, potentially translatable treatment strategies. Current advancements in experimental techniques have the potential to inform and validate dynamic mathematical models in an unprecedented manner to further enhance the predictive power of various disease models.
Focusing in the future, data-driven mathematical models can serve as useful tools to identify and test various regulatory mechanisms controlling population and single cell-level experimental observations. However, usage of quantitative models for non-intuitive experimental and pathological observations remains sparse. Research focusing on tumor growth dynamics in-vitro/in-vivo PDX systems can explore systems-level interplay of various signaling pathways in the tumor cells. Whereas expression levels of key pathway intermediates in individual or multicellular organisms can explain distinct proliferation capacity of individual tumors. Also psychiatric disorders and neurodegenerative diseases like Alzheimer’s disease or Parkinson’s disease exhibit diverse signaling, cellular and synaptic properties and transmitter system abnormalities, so understanding the underlying biological factors and links to neural computations will help determine where and how to focus research and treatment. Such as non-invasive brain stimulation (NIBS) techniques.
The goal of this research topic is to report on interdisciplinary studies comprising mathematical models that aim to further our understanding on working principles of small and/or large-scale regulatory pathways in healthy and diseased conditions facilitating targeted selection for interventions. We welcome studies involving, but not limited to:
- Model calibration-validation cycles comparing physiological and pathological states.
- Usage of new multidisciplinary approaches to understanding brain health
- Etiology, pathogenesis and progression mechanisms
- Early diagnosis including biomarkers, bio-imaging, and biosensors
- Examples like non-invasive brain stimulation (NIBS) to diagnosis and treatment coupled to mechanistic modelling to better understand brain health
We aim to further our understanding on systems-level working principles of signaling pathways and their modulation in health and disease.
Keywords:
Signaling pathways, Quantitative mechanistic studies, Neurodegenerative diseases, Psychiatric disorders, Non-invasive brain stimulation, Mathematical models
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.
Data-driven modelling of biological networks dramatically improved our understanding on the mechanistic casualties of various intra- and inter-cellular behaviour of living systems. For example, systems-level models of cellular signaling networks like in healthy and diseased brain cells or cancer tumors will continue to be highly valuable tools allowing incorporation of sufficient biological details and exhibit physiological validity to serve as explanatory tools. Similarly, data-driven models comparing aberration of regulatory pathways in healthy and diseased states can provide valuable mechanistic insights into novel, potentially translatable treatment strategies. Current advancements in experimental techniques have the potential to inform and validate dynamic mathematical models in an unprecedented manner to further enhance the predictive power of various disease models.
Focusing in the future, data-driven mathematical models can serve as useful tools to identify and test various regulatory mechanisms controlling population and single cell-level experimental observations. However, usage of quantitative models for non-intuitive experimental and pathological observations remains sparse. Research focusing on tumor growth dynamics in-vitro/in-vivo PDX systems can explore systems-level interplay of various signaling pathways in the tumor cells. Whereas expression levels of key pathway intermediates in individual or multicellular organisms can explain distinct proliferation capacity of individual tumors. Also psychiatric disorders and neurodegenerative diseases like Alzheimer’s disease or Parkinson’s disease exhibit diverse signaling, cellular and synaptic properties and transmitter system abnormalities, so understanding the underlying biological factors and links to neural computations will help determine where and how to focus research and treatment. Such as non-invasive brain stimulation (NIBS) techniques.
The goal of this research topic is to report on interdisciplinary studies comprising mathematical models that aim to further our understanding on working principles of small and/or large-scale regulatory pathways in healthy and diseased conditions facilitating targeted selection for interventions. We welcome studies involving, but not limited to:
- Model calibration-validation cycles comparing physiological and pathological states.
- Usage of new multidisciplinary approaches to understanding brain health
- Etiology, pathogenesis and progression mechanisms
- Early diagnosis including biomarkers, bio-imaging, and biosensors
- Examples like non-invasive brain stimulation (NIBS) to diagnosis and treatment coupled to mechanistic modelling to better understand brain health
We aim to further our understanding on systems-level working principles of signaling pathways and their modulation in health and disease.
Keywords:
Signaling pathways, Quantitative mechanistic studies, Neurodegenerative diseases, Psychiatric disorders, Non-invasive brain stimulation, Mathematical models
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.