The study of immunology is ultimately the study of networks. At the species level, host-pathogen interactions have been a major driving force of evolution and have left a legacy of genetic variation associated with susceptibility and resistance to disease. The microbial communities that live on and in us continue to influence disease susceptibility in ways that we are just beginning to understand. Within an individual, genetics, gender, age, lifestyle choices, and environmental factors combine to dictate an individual’s homeostatic set point and their ability to return to this set point after perturbations such as injury or infection. Immune cells direct the development of tissues such as lymph nodes and subsequently depend on these structures to facilitate the physical contact that is a pre-required to generate an immune response. The fate of hematopoietic progenitor cells is decided by complex transcriptional programs, which are controlled by input from external signals and factors that currently appear stochastic. The plasticity of immune cells as they adapt to environmental signals is again controlled by transcriptional and metabolic programs whose study is complicated by the considerable redundancy and complexity of these networks. Understanding and harnessing these networks may be the key to developing novel immunomodulatory therapies and treating diseases of immune dysfunction.
Because immunological networks range from the macro to the micro, immunology is a particularly rich field for bioinformatics. Unfortunately, bioinformatics is still perceived as a niche or specialty sub-topic within this field and this perception limits the incorporation of bioinformatics into the immunologist’s portfolio of skills. This research topic focusses on the breadth of computational tools and resources that complement conventional in vitro and in vivo studies. At the macro level these range from evolutionary studies of selection on immune genes, to population level studies of genetic variants that highlight novel host-pathogen interactions, to using social networks to understand disease transmission. At the micro level these include using publically accessible databases to investigate leukocyte differentiation and activation, discovery of novel regulatory elements and using knowledge of transcriptional and metabolic networks to inform drug discovery. The goal of this research topic is to demonstrate the power and potential of incorporating bioinformatics into all elements of immunology research.
The study of immunology is ultimately the study of networks. At the species level, host-pathogen interactions have been a major driving force of evolution and have left a legacy of genetic variation associated with susceptibility and resistance to disease. The microbial communities that live on and in us continue to influence disease susceptibility in ways that we are just beginning to understand. Within an individual, genetics, gender, age, lifestyle choices, and environmental factors combine to dictate an individual’s homeostatic set point and their ability to return to this set point after perturbations such as injury or infection. Immune cells direct the development of tissues such as lymph nodes and subsequently depend on these structures to facilitate the physical contact that is a pre-required to generate an immune response. The fate of hematopoietic progenitor cells is decided by complex transcriptional programs, which are controlled by input from external signals and factors that currently appear stochastic. The plasticity of immune cells as they adapt to environmental signals is again controlled by transcriptional and metabolic programs whose study is complicated by the considerable redundancy and complexity of these networks. Understanding and harnessing these networks may be the key to developing novel immunomodulatory therapies and treating diseases of immune dysfunction.
Because immunological networks range from the macro to the micro, immunology is a particularly rich field for bioinformatics. Unfortunately, bioinformatics is still perceived as a niche or specialty sub-topic within this field and this perception limits the incorporation of bioinformatics into the immunologist’s portfolio of skills. This research topic focusses on the breadth of computational tools and resources that complement conventional in vitro and in vivo studies. At the macro level these range from evolutionary studies of selection on immune genes, to population level studies of genetic variants that highlight novel host-pathogen interactions, to using social networks to understand disease transmission. At the micro level these include using publically accessible databases to investigate leukocyte differentiation and activation, discovery of novel regulatory elements and using knowledge of transcriptional and metabolic networks to inform drug discovery. The goal of this research topic is to demonstrate the power and potential of incorporating bioinformatics into all elements of immunology research.
