About this Research Topic
Understanding biologic complexity is at a crossroads as the enormous knowledge gathered during decades of reductionist scientific investigation now needs to be integrated in order to answer the critical questions facing biomedicine today. To predict developmental pathways and phenotype, disease, and treatment outcomes are essential goals. Thus far, inroads have been made through network modeling and an appreciation of systems phenomena such as feedback loops, ultrasensitivity, and bistability and how these principles effect life processes have been gained.
Today, studies at the molecular level are being shown to encode systems level changes. For example, dynamic abundance of a phosphatase can alter tumoricidal activity of NK cells. In a more compelling example, switching of transcriptional programs from an interferon (IFN)-responsive cell to an IFN-secreting cell was dependent on certain enzymatic activity.
Presently, the aim of this Research Topic is to gather current studies in cell and developmental biology that capture the molecular biologic processes that encode systems level changes. For example, does protein quantify alter phenotypic outcomes? Thus, characterizing signal pathways quantitatively with key tools such as single molecule resolution microscopy, biosensor design, and cell tracking and image analysis software will be of interest. Mathematical models specifically addressing network dynamics will further enhance the Topic.
We welcome the following article types: Brief Research Report, Correction, Data Report, Editorial, General Commentary, Hypothesis & Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Review, Technology and Code.
Topics of interest for this Research Topic include but are not limited to:
Quantitative models of signaling dynamics
Dynamic regulation cell proliferation and differentiation
Inflammatory and immune signaling
Cell-cell communication
DNA damage response
Synthetic biology
Multi-scale modeling
Today, studies at the molecular level are being shown to encode systems level changes. For example, dynamic abundance of a phosphatase can alter tumoricidal activity of NK cells. In a more compelling example, switching of transcriptional programs from an interferon (IFN)-responsive cell to an IFN-secreting cell was dependent on certain enzymatic activity.
Presently, the aim of this Research Topic is to gather current studies in cell and developmental biology that capture the molecular biologic processes that encode systems level changes. For example, does protein quantify alter phenotypic outcomes? Thus, characterizing signal pathways quantitatively with key tools such as single molecule resolution microscopy, biosensor design, and cell tracking and image analysis software will be of interest. Mathematical models specifically addressing network dynamics will further enhance the Topic.
We welcome the following article types: Brief Research Report, Correction, Data Report, Editorial, General Commentary, Hypothesis & Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Review, Technology and Code.
Topics of interest for this Research Topic include but are not limited to:
Quantitative models of signaling dynamics
Dynamic regulation cell proliferation and differentiation
Inflammatory and immune signaling
Cell-cell communication
DNA damage response
Synthetic biology
Multi-scale modeling
Keywords: Systems biology, quantitative modeling, dynamic networks, signaling pathways, mathematical modeling
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