What is he best known for?
The fields of study he is best known for:
Andrew G. Bowie focuses on Signal transduction, Cell biology, Molecular biology, Innate immune system and Receptor.
His Signal transduction research includes elements of Interferon, Transcription factor and Toll-like receptor.
His study in TIRAP and Myeloid Differentiation Factor 88 is carried out as part of his studies in Toll-like receptor.
His work deals with themes such as Cell, TRIF and Immune system, Immunity, which intersect with Cell biology.
The concepts of his Molecular biology study are interwoven with issues in I-Kappa-B Kinase, DNA, AIM2, Mediator and IFI16.
His research brings together the fields of Immunology and Receptor.
His most cited work include:
- The family of five: TIR-domain-containing adaptors in Toll-like receptor signalling (1982 citations)
- IFI16 is an innate immune sensor for intracellular DNA. (1093 citations)
- Mal (MyD88-adapter-like) is required for Toll-like receptor-4 signal transduction (1087 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Innate immune system, Cell biology, Signal transduction, Pattern recognition receptor and Immunology.
Andrew G. Bowie has included themes like Interferon, Virology and Immunity in his Innate immune system study.
His work carried out in the field of Cell biology brings together such families of science as Cell, Cell culture, Cytokine, Transcription factor and DNA.
His Signal transduction research incorporates elements of Molecular biology and Toll-like receptor, TRIF.
While the research belongs to areas of Pattern recognition receptor, he spends his time largely on the problem of RIG-I, intersecting his research to questions surrounding RNA silencing.
His work in Signal transducing adaptor protein addresses subjects such as Myeloid Differentiation Factor 88, which are connected to disciplines such as TIRAP.
He most often published in these fields:
- Innate immune system (46.27%)
- Cell biology (44.03%)
- Signal transduction (30.60%)
What were the highlights of his more recent work (between 2014-2021)?
- Innate immune system (46.27%)
- Cell biology (44.03%)
- Cytokine (11.94%)
In recent papers he was focusing on the following fields of study:
Andrew G. Bowie spends much of his time researching Innate immune system, Cell biology, Cytokine, Interferon and Immunology.
His research in Innate immune system intersects with topics in Proinflammatory cytokine, Signal transduction and Pseudogene.
His Signal transduction research incorporates themes from Regulator and Toll-like receptor.
His Toll-like receptor study deals with TLR2 intersecting with Cell signaling.
He interconnects DNA, Programmed cell death and Immune system in the investigation of issues within Cell biology.
He works mostly in the field of Interferon, limiting it down to topics relating to IFI16 and, in certain cases, Ubiquitin, Gene induction and Molecular biology, as a part of the same area of interest.
Between 2014 and 2021, his most popular works were:
- The Vaccine Adjuvant Chitosan Promotes Cellular Immunity via DNA Sensor cGAS-STING-Dependent Induction of Type I Interferons (232 citations)
- IFI16 and cGAS cooperate in the activation of STING during DNA sensing in human keratinocytes (147 citations)
- Innate immune recognition of DNA: A recent history (144 citations)
In his most recent research, the most cited papers focused on:
Andrew G. Bowie focuses on Cell biology, Innate immune system, DNA, IFI16 and Sting.
His Cell biology study integrates concerns from other disciplines, such as Secretion, Depolarization and Immune system, Immunity.
The Innate immune system study combines topics in areas such as Pyroptosis, Inflammasome, Programmed cell death, Cytokine and Lipopolysaccharide.
DNA is closely attributed to Transcription factor in his study.
His research integrates issues of Interferon, Pattern recognition receptor, Ubiquitin and DNA damage in his study of IFI16.
In his work, he performs multidisciplinary research in Sting and Molecular biology.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
