Bioinformatics and Genomic Networks
Bioinformatics and Genomic Networks is a research topic within Molecular Biology. Science Explorer counts 37k research works in it since 1950. 9.9% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the analysis and interpretation of gene interaction networks, including gene set enrichment analysis, protein-protein interaction networks, functional annotation, pathway analysis, biological network integration, co-expression networks, disease pathways, genomic data integration, and the development of Cytoscape plugins. The research aims to understand the functional organization of genes and proteins within cellular systems and their implications for human diseases.
- Gene Set Enrichment Analysis
- Protein-Protein Interaction Networks
- Functional Annotation
- Pathway Analysis
- Biological Network Integration
- Co-expression Networks
- Disease Pathways
- Genomic Data Integration
- Cytoscape Plugins
- Human Protein Interactome
- Research works
- 37k fractional, since 1950
- In the world top 10%
- 3.6k per year above
- Top-10% rate
- 9.9% share of its works in the world top 10%
- Growth, 2018-21 → 2022-25
- +8% the tick is no change
- Largest producer
China
36% of the 10 largest, 2022-now
Which countries lead Bioinformatics and Genomic Networks research?
By volume, China and the United States publish the most (2.5k and 2.1k works in 2022-now).
By volume, 2022-now
- 1
China 2.5k works
- 2
United States 2.1k works
- 3
India 652 works
- 4
United Kingdom 331 works
- 5
Germany 329 works
- 6
Italy 241 works
- 7
France 206 works
- 8
Canada 182 works
- 9
South Korea 164 works
- 10
Japan 157 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 Bioinformatics and Genomic Networks research?
By volume in 2022-now, Harvard University publishes the most Bioinformatics and Genomic Networks research, followed by Chinese Academy of Sciences and Centre National de la Recherche Scientifique.
By volume, 2022-now
- 1
Harvard University
United States 106 works
- 2
Chinese Academy of Sciences
China 89 works
- 3
Centre National de la Recherche Scientifique
France 57 works
- 4
Central South University
China 48 works
- 5
National Institutes of Health
United States 47 works
- 6
University of North Carolina at Chapel Hill
United States 47 works
- 7
Shanghai Jiao Tong University
China 41 works
- 8
Zhejiang University
China 39 works
- 9
Stanford University
United States 36 works
- 10
Sun Yat-sen University
China 36 works
Who are the leading researchers in Bioinformatics and Genomic Networks?
The most-cited researchers publishing on Bioinformatics and Genomic Networks include Eric S. Lander, Zhong Lin Wang and Yoshua Bengio.
- 1
Eric S. Lander
United States 524k citations
- 2
Zhong Lin Wang
United States 491k citations
- 3
Yoshua Bengio
Canada 476k 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 Bioinformatics and Genomic Networks research done?
The largest centres of Bioinformatics and Genomic Networks research in 2022-now are Beijing (China), Shanghai (China), Guangzhou (China) and Changsha (China). Among places with at least 20 works in it, it is an unusually large share of all research in Catanzaro, Indianapolis and Cambridge.
Largest cities, 2022-now
Where it is the local speciality
- CatanzaroIT · 25.7 works29×
- IndianapolisUS · 20.9 works3.9×
- CambridgeGB · 53.2 works3.8×
- CambridgeUS · 81.3 works3.7×
- BethesdaUS · 38.0 works3.7×
Location quotient: how much more of its research is in Bioinformatics and Genomic Networks than the world average.
Where is the best place to study Bioinformatics and Genomic Networks?
Among universities, judged by research, Harvard University, Massachusetts Institute of Technology and Stanford 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.
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 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 Bioinformatics and Genomic Networks, country by countryIs Bioinformatics and Genomic Networks research growing?
Output in 2022-2025 was 8% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Bioinformatics and Genomic Networks.
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 Bioinformatics and Genomic Networks as a percentage of every work published that year, 0.033% in 2024.
Fractional works of Bioinformatics and Genomic Networks 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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