Genetic Associations and Epidemiology
Genetic Associations and Epidemiology is a research topic within Genetics. Science Explorer counts 28k research works in it since 1950. 9.7% of them reached the world's top 10% most cited for their field and year.
This cluster of papers encompasses a wide range of topics in genomic studies, including genome-wide association analyses, genetic variation, haplotype mapping, population genetics, Mendelian randomization, polygenic risk scores, gene expression, and the study of complex diseases. It explores methods for analyzing genetic data and understanding the genetic basis of various traits and diseases.
- Genome-wide Association
- Genetic Variation
- Haplotype Mapping
- Population Genetics
- Mendelian Randomization
- Polygenic Risk Scores
- Gene Expression
- Complex Diseases
- Linkage Disequilibrium
- Human Genomics
- Research works
- 28k fractional, since 1950
- In the world top 10%
- 2.8k per year above
- Top-10% rate
- 9.7% share of its works in the world top 10%
- Growth, 2018-21 → 2022-25
- +47% the tick is no change
- Largest producer
China
41% of the 10 largest, 2022-now
Which countries lead Genetic Associations and Epidemiology research?
By volume, China and the United States publish the most (2.9k and 2.3k works in 2022-now).
By volume, 2022-now
- 1
China 2.9k works
- 2
United States 2.3k works
- 3
United Kingdom 573 works
- 4
Germany 220 works
- 5
Canada 202 works
- 6
Australia 179 works
- 7
South Korea 173 works
- 8
India 171 works
- 9
Netherlands 149 works
- 10
Spain 133 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.
Shares of the rows listed above, not of the whole node.
Which institutions lead Genetic Associations and Epidemiology research?
By volume in 2022-now, Harvard University publishes the most Genetic Associations and Epidemiology research, followed by University of North Carolina at Chapel Hill and Sichuan University.
By volume, 2022-now
- 1
Harvard University
United States 193 works
- 2
University of North Carolina at Chapel Hill
United States 127 works
- 3
Sichuan University
China 91 works
- 4
Central South University
China 76 works
- 5
National Institutes of Health
United States 71 works
- 6
Zhejiang University
China 66 works
- 7
Nanjing Medical University
China 63 works
- 8
Sun Yat-sen University
China 62 works
- 9
University of Pennsylvania
United States 62 works
- 10
Shanghai Jiao Tong University
China 58 works
Who are the leading researchers in Genetic Associations and Epidemiology?
The most-cited researchers publishing on Genetic Associations and Epidemiology include David Moher, Douglas G. Altman and Eric S. Lander.
- 1
David Moher
Canada 898k citations
- 2
Douglas G. Altman
United Kingdom 862k citations
- 3
Eric S. Lander
United States 524k citations
- 4
Rob Knight
United States 468k citations
- 5
George Davey Smith
United Kingdom 435k citations
- 6
Walter Churchill Willett
United States 411k citations
- 7
Richard M. Durbin
United Kingdom 410k citations
- 8
Mark J. Daly
United States 403k citations
- 9
Stacey L. Gabriel
United States 402k citations
- 10
Peer Bork
Germany 396k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Genetic Associations and Epidemiology research done?
The largest centres of Genetic Associations and Epidemiology research in 2022-now are Beijing (China), Guangzhou (China), London (United Kingdom) and Shanghai (China). Among places with at least 20 works in it, it is an unusually large share of all research in Chapel Hill and Bristol.
Largest cities, 2022-now
- 1
Beijing
China 343 works
- 2
Guangzhou
China 205 works
- 3
London
United Kingdom 195 works
- 4
Shanghai
China 183 works
- 5
Chengdu
China 145 works
- 6
Hangzhou
China 135 works
- 7
New York
United States 133 works
- 8
Chapel Hill
United States 126 works
- 9
Boston
United States 122 works
- 10
Cambridge
United States 122 works
Where it is the local speciality
- Chapel HillUS · 125.6 works8.3×
- BristolGB · 49.5 works6.6×
Location quotient: how much more of its research is in Genetic Associations and Epidemiology than the world average.
Where is the best place to study Genetic Associations and Epidemiology?
Among universities, judged by research, Harvard University, University of Cambridge and University of Oxford score highest, combining citation excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.
Universities only. The score blends citation excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.
Every institution in Genetic Associations and Epidemiology, country by countryIs Genetic Associations and Epidemiology research growing?
Output in 2022-2025 was 47% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Genetic Associations and Epidemiology.
The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.
Its share of all research
Growing output can still be a shrinking share: all of science grows. This is Genetic Associations and Epidemiology as a percentage of every work published that year, 0.035% in 2024.
Fractional works of Genetic Associations and Epidemiology over all fractional works that year. How the balance of science has shifted.
How much of it reaches the world top 10%
Year by year.
Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.
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.
Discussion
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