Systems Immunology Approaches in Infectious Diseases
A special issue of Biology (ISSN 2079-7737). This special issue belongs to the section "Immunology".
Deadline for manuscript submissions: closed (28 February 2021) | Viewed by 4826
Special Issue Editors
Interests: quantitative virology; quantitative immunology; coinfection biology; infectious diseases; mathematical modeling
2. Faculty of Life Sciences and Medicine, King's College London, London WC2R 2LS, UK
Interests: immunology; liver disease; biostatistics; gut-body axis
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Special Issue Information
Dear Colleagues,
With the advent of advanced molecular technologies, a massive amount of immunological data is now available in the field of infectious diseases. In addition, the scale and complexity of analysis have grown along with the large dimension of these datasets. As a result, systematic investigation using quantitative tools such as bioinformatics, mathematical, and statistical modeling are playing a critical role in providing accurate approximations of the complicated patterns in immunological data. Thus, incorporating and applying mathematics, computer science, engineering, and biology, the Systems Biology approach allows a simplified representation of the complex host–pathogen interactions during infections and enhances our ability to investigate and combat diseases, all with increased accuracy, timeliness, and efficiency.
This research topic will be designed to feature the latest novel findings about molecular and cellular mechanisms of host antiviral defense from high-throughput experimental methodologies to computational and theoretical approaches. All papers will be comprised of multidisciplinary approaches to handling the existing challenges faced in this fast-growing field. The vision of this Special Issue is to bring clinicians; engineers; basic scientists such as biologists, immunologists, physicists, and mathematicians; and big data analytics together to provide readers with the current state of the art of systems biology approaches in understanding immunity against pathogens, and aiding the development of antiviral therapies.
Dr. Lubna Pinky
Dr. Antonio Riva
Guest Editors
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Keywords
- innate and adaptive immunity
- multi-pathogen infections or coinfections
- antimicrobial resistance
- emerging infectious diseases
- genomic, proteomic, and metabolic analysis
- imaging
- machine learning techniques
- computational modeling
- nonlinear analysis
- statistical analysis
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