What is she best known for?
The fields of study she is best known for:
Her primary areas of study are Mycobacterium tuberculosis, Tuberculosis, Microbiology, Genetics and Virology.
The various areas that Brigitte Gicquel examines in her Mycobacterium tuberculosis study include DC-SIGN and Gene, Mutant, Virulence.
Her research integrates issues of Immunology, Polymerase chain reaction and Gene expression profiling in her study of Tuberculosis.
Her Microbiology study integrates concerns from other disciplines, such as Mycobacterium, Mycobacterium fortuitum, Secretion and Cytoplasm.
The Mycobacterium study which covers Biochemistry that intersects with Mycobacterium smegmatis and Antigen.
Her Virology research is multidisciplinary, incorporating elements of Mycobacterium tuberculosis complex, Antibiotics and Guinea pig.
Her most cited work include:
- DC-SIGN Is the Major Mycobacterium tuberculosis Receptor on Human Dendritic Cells (554 citations)
- Identification of a virulence gene cluster of Mycobacterium tuberculosis by signature‐tagged transposon mutagenesis (554 citations)
- Variable human minisatellite-like regions in the Mycobacterium tuberculosis genome. (483 citations)
What are the main themes of her work throughout her whole career to date?
Mycobacterium tuberculosis, Microbiology, Tuberculosis, Virology and Gene are her primary areas of study.
Her biological study spans a wide range of topics, including Genetics, Mutant, Immunology and Virulence.
Her work carried out in the field of Microbiology brings together such families of science as Mutation, Innate immune system and Mycobacterium, Bacteria.
Her Tuberculosis research incorporates elements of Attenuated vaccine, Disease and Immunity.
The Virology study combines topics in areas such as Genotype, Multiple drug resistance and Antigen, Immunogenicity.
Her Gene study combines topics in areas such as Molecular biology and Mycobacterium smegmatis.
She most often published in these fields:
- Mycobacterium tuberculosis (55.48%)
- Microbiology (44.88%)
- Tuberculosis (39.93%)
What were the highlights of her more recent work (between 2010-2020)?
- Mycobacterium tuberculosis (55.48%)
- Tuberculosis (39.93%)
- Microbiology (44.88%)
In recent papers she was focusing on the following fields of study:
Her primary scientific interests are in Mycobacterium tuberculosis, Tuberculosis, Microbiology, Immunology and Immune system.
Brigitte Gicquel has included themes like Genetics, Typing, Virology, Wild type and Virulence in her Mycobacterium tuberculosis study.
Her Tuberculosis study incorporates themes from Internal medicine, Disease and Immunity.
Her study in Microbiology is interdisciplinary in nature, drawing from both Innate immune system, Efflux and Mycobacterium aurum.
Her research in Immunology intersects with topics in Tuberculosis vaccines and Adenosine.
She combines subjects such as Interferon, Antigen and Cell biology with her study of Immune system.
Between 2010 and 2020, her most popular works were:
- Mycobacterium abscessus: a new antibiotic nightmare (392 citations)
- Recombinant BCG Expressing LTAK63 Adjuvant induces Superior Protection against Mycobacterium tuberculosis. (251 citations)
- Mycobacterial P1-Type ATPases Mediate Resistance to Zinc Poisoning in Human Macrophages (216 citations)
In her most recent research, the most cited papers focused on:
The scientist’s investigation covers issues in Mycobacterium tuberculosis, Microbiology, Tuberculosis, Genetics and Immunology.
Her Mycobacterium tuberculosis research focuses on Virulence and how it relates to Virology, Promoter activity, Beijing family and Strain.
Her Microbiology research incorporates themes from Mycobacterium bovis, Dehydratase, Innate immune system, Immune system and Mycolic acid.
Her studies deal with areas such as Cancer research, Methyltransferase and Neovascularization as well as Tuberculosis.
Her Immunology research integrates issues from Wild type and Angiogenesis.
Her Gene study combines topics from a wide range of disciplines, such as Evolutionary biology, Mycobacterium tuberculosis complex and Genetic diversity.
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.
