About this Research Topic
Infectious diseases are latent threats to humankind – annually killing 16 million people worldwide. Understanding infectious diseases and their transmission is a central vexation for science - but this involves complex, dynamic, and multi-scale processes. Thus, a range of systematic and tractable approaches that integrate a variety of research data on multiple scales into mathematical and computational models are crucial to harnessing molecular knowledge of infectious diseases and the respective immune responses at a within-host level, as well as the spatial and temporal interactions that are determinant for infection transmission.
The proposed Research Topic will bring together the current state of the art on computational models covering processes on multiple temporal and/or spatial scales (e.g. genes, molecular, cells, tissues, organs, individual and population) and in combination with experimental data. It is envisaged that an iterative process intertwining multiscale computational approaches and experiments will refine and progressively fine-tune the multiscale models, thereby enabling the generation of more accurate hypotheses. This knowledge-based on multiscale in silico tools is fundamental steps forward uncovering the hidden molecular processes that occur during infections and transmission. This draws on the philosophy that immune cell dynamics at the within-host level and contact-pattern between age groups have an underlying shape and that shape has an impact on infections and epidemics.
Therefore, manuscripts should address the experimental and theoretical aspects of the wider field of microbiology and immunology. While manuscripts addressing any infectious diseases are welcomed, we particularly focus on viral infections such as influenza, HIV, Dengue, Zika and Ebola. The inclusion of experimental data into computational approaches is highly required.
The proposed Research Topic aims to:
• bring together multiscale computational approaches that provide an accurate approximation to experimental data at the intracellular, cellular or individual level,
• construct multiscale models to further understanding the molecular basis of T cell responses during infection,
• integrate diverse next-generation omics platforms to guide therapies in infectious diseases,
• simulate disease transmission across scales -- from the infected host-dynamics to the population level,
• develop network models to dissect critical host molecular factors between different age groups as well as social contact-patterns that can be potentially used to prevent outbreaks and epidemics.
Manuscripts describing the muti-scale methodological progress that allows projecting computational models into measurable experimental outcomes are particularly welcome.
Article types welcomed: Reviews, Mini-Reviews, Original Research, Hypothesis and Theory
The proposed Research Topic will bring together the current state of the art on computational models covering processes on multiple temporal and/or spatial scales (e.g. genes, molecular, cells, tissues, organs, individual and population) and in combination with experimental data. It is envisaged that an iterative process intertwining multiscale computational approaches and experiments will refine and progressively fine-tune the multiscale models, thereby enabling the generation of more accurate hypotheses. This knowledge-based on multiscale in silico tools is fundamental steps forward uncovering the hidden molecular processes that occur during infections and transmission. This draws on the philosophy that immune cell dynamics at the within-host level and contact-pattern between age groups have an underlying shape and that shape has an impact on infections and epidemics.
Therefore, manuscripts should address the experimental and theoretical aspects of the wider field of microbiology and immunology. While manuscripts addressing any infectious diseases are welcomed, we particularly focus on viral infections such as influenza, HIV, Dengue, Zika and Ebola. The inclusion of experimental data into computational approaches is highly required.
The proposed Research Topic aims to:
• bring together multiscale computational approaches that provide an accurate approximation to experimental data at the intracellular, cellular or individual level,
• construct multiscale models to further understanding the molecular basis of T cell responses during infection,
• integrate diverse next-generation omics platforms to guide therapies in infectious diseases,
• simulate disease transmission across scales -- from the infected host-dynamics to the population level,
• develop network models to dissect critical host molecular factors between different age groups as well as social contact-patterns that can be potentially used to prevent outbreaks and epidemics.
Manuscripts describing the muti-scale methodological progress that allows projecting computational models into measurable experimental outcomes are particularly welcome.
Article types welcomed: Reviews, Mini-Reviews, Original Research, Hypothesis and Theory
Keywords: T cell response, Infectious Diseases, Mathematical modeling, multiscale, drug resistance, virus, bacteria
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.
