Science Explorer Interactive view Map
Topic · Microbiology

Microbial infections and disease research

Microbial infections and disease research is a research topic within Microbiology. Science Explorer counts 33k research works in it since 1950. 13.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the pathogenesis, virulence factors, antimicrobial resistance, and genomic sequencing of bacterial pathogens such as Mycoplasma and Pasteurella, particularly in the context of bovine respiratory disease and human cell line authentication. It also explores host-pathogen interactions, vaccine development, and the impact of bacterial infections on animal and human health.

  • Mycoplasma
  • Pasteurella
  • Bovine Respiratory Disease
  • Cell Line Authentication
  • Virulence Factors
  • Antimicrobial Resistance
  • Genomic Sequencing
  • Host-Pathogen Interactions
  • Pneumonia
  • Vaccine Development
Research works
33k
fractional, since 1950
In the world top 10%
4.3k
per year above
Top-10% rate
13.0%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+17%
the tick is no change

Which countries lead Microbial infections and disease research research?

By volume, the United States and China publish the most (751 and 731 works in 2022–2025).

By volume, 2022–2025

  1. 1 United States 751 works
  2. 2 China 731 works
  3. 3 India 283 works
  4. 4 Brazil 196 works
  5. 5 United Kingdom 145 works
  6. 6 Japan 126 works
  7. 7 Germany 121 works
  8. 8 Spain 121 works
  9. 9 France 121 works
  10. 10 Canada 115 works

How concentrated that is

The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.

United States: 27.7%China: 27.0%India: 10.4%Brazil: 7.2%6 others listed: 27.7%28%largest
United States751 · 27.7%China731 · 27.0%India283 · 10.4%Brazil196 · 7.2%6 others listed750 · 27.7%

Shares of the rows listed above, not of the whole node.

Which institutions lead Microbial infections and disease research research?

By volume in 2022–2025, Huazhong Agricultural University publishes the most Microbial infections and disease research research, followed by Kansas State University and Iowa State University.

By volume, 2022–2025

  1. 1 Huazhong Agricultural UniversityChina 27 works
  2. 2 Kansas State UniversityUnited States 25 works
  3. 3 Iowa State UniversityUnited States 19 works
  4. 4 University of Veterinary MedicineHungary 19 works
  5. 5 Texas A&M UniversityUnited States 19 works
  6. 6 University of California, DavisUnited States 18 works
  7. 7 Yangzhou UniversityChina 18 works
  8. 8 Ghent UniversityBelgium 18 works
  9. 9 University of MosulIraq 17 works
  10. 10 South China Agricultural UniversityChina 17 works

Where is Microbial infections and disease research research done?

The largest centres of Microbial infections and disease research research in 2022–2025 are Beijing (China), Wuhan (China), São Paulo (Brazil) and Guangzhou (China). Among places with at least 20 works in it, it is an unusually large share of all research in Manhattan.

Largest cities, 2022–2025

  1. 1 Beijing China 117 works
  2. 2 Wuhan China 55 works
  3. 3 São Paulo Brazil 43 works
  4. 4 Guangzhou China 42 works
  5. 5 Paris France 37 works
  6. 6 Tokyo Japan 36 works
  7. 7 Moscow Russia 36 works
  8. 8 Giza Egypt 31 works
  9. 9 Nanjing China 29 works
  10. 10 London United Kingdom 29 works

Where it is the local speciality

  1. ManhattanUS · 25.3 works26×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Microbial infections and disease research than the world average.

See Microbial infections and disease research on the map

Where is the best place to study Microbial infections and disease research?

Among universities, judged by research, Ghent University, Huazhong Agricultural University and Yangzhou University score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.

0%20%40%mean 16.41%fractional works in this node (log) →share in the world top 10% →Ghent University: 18, 26.9%Huazhong Agricultural University: 27, 14.6%Yangzhou University: 18, 29.8%South China Agricultural University: 17, 24.1%University of Saskatchewan: 16, 15.2%Kansas State University: 25, 5.9%Iowa State University: 20, 10.1%University of Veterinary Medicine: 19, 1.0%University of Veterinary and Animal Sciences: 11, 12.5%University of Copenhagen: 14, 24.0%Yangzhou UniversityGhent UniversitySouth China Agricult…Huazhong Agricultura…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Ghent UniversityBelgium 65.926.9%7.6×18 +21.0%
2 Huazhong Agricultural UniversityChina 62.914.6%19.1×27 -6.4%
3 Yangzhou UniversityChina 62.829.8%7.7×18 -11.5%
4 South China Agricultural UniversityChina 60.224.1%11.2×17 -56.2%
5 University of SaskatchewanCanada 59.415.2%13.2×16 +37.7%
6 Kansas State UniversityUnited States 54.65.9%26.8×25 +15.9%
7 Iowa State UniversityUnited States 54.310.1%12.5×20 +12.3%
8 University of Veterinary MedicineHungary 53.11.0%77.0×19 +99.1%
9 University of Veterinary and Animal SciencesPakistan 51.812.5%37.9×11 +47.9%
10 University of CopenhagenDenmark 51.324.0%5.0×14 +3.4%

Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.

Is Microbial infections and disease research research growing?

Output in 2018–2022 was 17% higher than in 2013–2017, peaking in 2021. The fastest-growing topics are Microbial infections and disease research.

19801990200020102020
grewheldshrank

The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.

Which topics inside it are moving

Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.