What is he best known for?
The fields of study he is best known for:
His main research concerns Paratuberculosis, Microbiology, Restriction fragment length polymorphism, Veterinary medicine and Mycobacterium.
His Paratuberculosis research integrates issues from Herd, Feces, Raw milk and Emaciation.
His Microbiology research includes elements of Lymph, Virology, Polymerase chain reaction and Insertion sequence.
In his research on the topic of Veterinary medicine, Disease, Bubalus arnee and Wild boar is strongly related with Livestock.
Ivo Pavlik has included themes like Mycobacterium tuberculosis complex, Mycobacterium caprae and Contamination in his Mycobacterium study.
His Genotype study combines topics from a wide range of disciplines, such as Lumbricidae, Typing and DNA profiling.
His most cited work include:
- Bovine tuberculosis: an old disease but a new threat to Africa. (346 citations)
- Epidemiological Study of Paratuberculosis in Wild Rabbits in Scotland (170 citations)
- Mycobacterium avium subspecies paratuberculosis cultured from locally and commercially pasteurized cow's milk in the Czech Republic. (168 citations)
What are the main themes of his work throughout his whole career to date?
Ivo Pavlik spends much of his time researching Microbiology, Mycobacterium, Paratuberculosis, Veterinary medicine and Virology.
His work in Microbiology addresses issues such as Restriction fragment length polymorphism, which are connected to fields such as DNA profiling and Restriction enzyme.
Mycobacterium is a subfield of Tuberculosis that Ivo Pavlik tackles.
His biological study spans a wide range of topics, including Dairy cattle, Herd and Feces.
The Veterinary medicine study combines topics in areas such as Mycobacterium bovis, Outbreak and Roe deer.
His work in Virology covers topics such as Hepatitis E virus which are related to areas like Hepatitis E.
He most often published in these fields:
- Microbiology (43.03%)
- Mycobacterium (35.25%)
- Paratuberculosis (33.20%)
What were the highlights of his more recent work (between 2016-2019)?
- Microbiology (43.03%)
- Mycobacterium (35.25%)
- Veterinary medicine (23.77%)
In recent papers he was focusing on the following fields of study:
Microbiology, Mycobacterium, Veterinary medicine, Paratuberculosis and Tuberculosis are his primary areas of study.
His Microbiology study incorporates themes from Multiplex polymerase chain reaction, Polymerase chain reaction, Restriction enzyme and Mixed infection.
He studied Mycobacterium and Feces that intersect with Restriction fragment length polymorphism, Transmission and Animal science.
His Veterinary medicine study combines topics in areas such as Livestock and Mycobacterium bovis.
Ivo Pavlik focuses mostly in the field of Paratuberculosis, narrowing it down to topics relating to Disease and, in certain cases, Immunology.
His biological study deals with issues like Staining, which deal with fields such as Granuloma.
Between 2016 and 2019, his most popular works were:
- Alternatives to antibiotic growth promoters in prevention of diarrhoea in weaned piglets: a review. (113 citations)
- The transmission and impact of paratuberculosis infection in domestic and wild ruminants (103 citations)
- Economic impact of paratuberculosis in dairy cattle herds: a review (85 citations)
In his most recent research, the most cited papers focused on:
His scientific interests lie mostly in Veterinary medicine, Herd, Microbiology, Paratuberculosis and Mycobacterium bovis.
The study incorporates disciplines such as Oryx, Bison bison, Tuberculin, Livestock and Canis in addition to Veterinary medicine.
His work deals with themes such as Incidence, Mixed infection, Mycobacterium, Trichogaster and Aquarium fish, which intersect with Microbiology.
His Mycobacterium research is multidisciplinary, relying on both Baby food and Public health.
His Paratuberculosis research includes elements of Dairy cattle, Feces and Disease.
His studies in Mycobacterium bovis integrate themes in fields like BCG vaccine, Molecular epidemiology, Outbreak and Virulence.
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.
