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. 20.5% 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%
- 7.5k per year above
- Top-10% rate
- 20.5% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +14% the tick is no change
Which countries lead Bioinformatics and Genomic Networks research?
By volume, China and the United States publish the most (2.1k and 1.7k works in 2022–2025).
By volume, 2022–2025
- 1 China 2.1k works
- 2 United States 1.7k works
- 3 India 538 works
- 4 Germany 281 works
- 5 United Kingdom 279 works
- 6 Italy 213 works
- 7 France 176 works
- 8 Canada 158 works
- 9 South Korea 136 works
- 10 Japan 132 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 2022–2025, Harvard University publishes the most Bioinformatics and Genomic Networks research, followed by Central South University and University of North Carolina at Chapel Hill.
By volume, 2022–2025
- 1 Harvard UniversityUnited States 36 works
- 2 Central South UniversityChina 36 works
- 3 University of North Carolina at Chapel HillUnited States 34 works
- 4 Chinese Academy of SciencesChina 28 works
- 5 University of PennsylvaniaUnited States 25 works
- 6 Stanford UniversityUnited States 24 works
- 7 Magna Graecia UniversityItaly 24 works
- 8 Shanghai Jiao Tong UniversityChina 23 works
- 9 Shandong UniversityChina 23 works
- 10 Northwestern Polytechnical UniversityChina 23 works
Who are the leading researchers in Bioinformatics and Genomic Networks?
The most-cited researchers publishing on Bioinformatics and Genomic Networks include Robert Tibshirani, Mark J. Daly and Eric S. Lander.
- 1 Robert Tibshirani United States 13k citations
- 2 Mark J. Daly United States 9.6k citations
- 3 Eric S. Lander United States 8.5k citations
- 4 John P. A. Ioannidis United States 8k citations
- 5 Benjamin M. Neale United States 7.9k citations
- 6 Stacey Gabriel United States 7.8k citations
- 7 Vamsi K. Mootha United States 6.9k citations
- 8 David Botstein United States 6.7k citations
- 9 Philip S. Yu United States 6.6k citations
- 10 Pablo Tamayo United States 6.5k 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 2022–2025 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, Cambridge and Cambridge.
Largest cities, 2022–2025
Where it is the local speciality
- CatanzaroIT · 24.7 works33×
- CambridgeUS · 69.7 works3.9×
- CambridgeGB · 43.8 works3.7×
- BethesdaUS · 32.0 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, Magna Graecia University and Qufu Normal 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 table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Harvard UniversityUnited States | 58.0 | 28.3% | 4.1× | 36 | +2.2% |
| 2 | Magna Graecia UniversityItaly | 57.0 | 12.6% | 34.7× | 24 | +47.0% |
| 3 | Qufu Normal UniversityChina | 57.0 | 12.2% | 11.4× | 14 | +689.5% |
| 4 | Icahn School of Medicine at Mount SinaiUnited States | 53.7 | 25.8% | 5.5× | 19 | +83.3% |
| 5 | University of Chinese Academy of SciencesChina | 52.3 | 28.7% | 1.7× | 20 | +186.3% |
| 6 | University of PennsylvaniaUnited States | 52.1 | 25.4% | 3.9× | 25 | +76.1% |
| 7 | Stanford UniversityUnited States | 51.9 | 32.8% | 2.9× | 24 | +21.2% |
| 8 | Central South UniversityChina | 50.6 | 23.4% | 3.0× | 36 | +48.7% |
| 9 | Harbin Medical UniversityChina | 50.5 | 15.3% | 13.4× | 19 | -14.5% |
| 10 | Michigan State UniversityUnited States | 49.3 | 42.0% | 2.8× | 14 | +5.3% |
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 Bioinformatics and Genomic Networks research growing?
Output in 2018–2022 was 14% higher than in 2013–2017, 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.
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.