Gene Regulatory Network Analysis
Gene Regulatory Network Analysis is a research topic within Molecular Biology. Science Explorer counts 28k research works in it since 1950. 17.8% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on the stochastic behavior and regulation of gene networks, exploring topics such as stochastic gene expression, synthetic biology, cellular noise, network inference, genetic circuits, biochemical modeling, cell signaling dynamics, and single-cell analysis. The research delves into understanding the inherent stochasticity in gene regulatory networks and its implications for cellular functions.
- Stochastic Gene Expression
- Gene Regulatory Networks
- Synthetic Biology
- Cellular Noise
- Systems Biology
- Network Inference
- Genetic Circuits
- Biochemical Modeling
- Cell Signaling Dynamics
- Single-Cell Analysis
- Research works
- 28k fractional, since 1950
- In the world top 10%
- 5k per year above
- Top-10% rate
- 17.8% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- -9% the tick is no change
Which countries lead Gene Regulatory Network Analysis research?
By volume, the United States and China publish the most (1k and 855 works in 2022–2025).
By volume, 2022–2025
- 1 United States 1k works
- 2 China 855 works
- 3 Germany 235 works
- 4 United Kingdom 214 works
- 5 France 197 works
- 6 India 167 works
- 7 Italy 144 works
- 8 Japan 143 works
- 9 Spain 85 works
- 10 Canada 78 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 Gene Regulatory Network Analysis research?
By volume in 2022–2025, Shandong Normal University publishes the most Gene Regulatory Network Analysis research, followed by Centre National de la Recherche Scientifique and Shandong University.
By volume, 2022–2025
- 1 Shandong Normal UniversityChina 30 works
- 2 Centre National de la Recherche ScientifiqueFrance 26 works
- 3 Shandong UniversityChina 25 works
- 4 University of California San DiegoUnited States 21 works
- 5 Imperial College LondonUnited Kingdom 21 works
- 6 University of OxfordUnited Kingdom 20 works
- 7 Southeast UniversityChina 18 works
- 8 Shanghai Jiao Tong UniversityChina 17 works
- 9 Huazhong University of Science and TechnologyChina 17 works
- 10 The University of TokyoJapan 16 works
Who are the leading researchers in Gene Regulatory Network Analysis?
The most-cited researchers publishing on Gene Regulatory Network Analysis include Ian F. Akyildiz, David Botstein and Minoru Kanehisa.
- 1 Ian F. Akyildiz United States 8.2k citations
- 2 David Botstein United States 6.7k citations
- 3 Minoru Kanehisa Japan 5.7k citations
- 4 Guanrong Chen Hong Kong 5.4k citations
- 5 Zidong Wang United Kingdom 4.4k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Gene Regulatory Network Analysis research done?
The largest centres of Gene Regulatory Network Analysis research in 2022–2025 are Beijing (China), Paris (France), Shanghai (China) and Jinan (China).
Where is the best place to study Gene Regulatory Network Analysis?
Among universities, judged by research, Shandong Normal University, California Institute of Technology and University of Delaware 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 | Shandong Normal UniversityChina | 63.6 | 5.9% | 30.2× | 30 | +1127.7% |
| 2 | California Institute of TechnologyUnited States | 62.5 | 33.6% | 16.1× | 15 | -27.3% |
| 3 | University of DelawareUnited States | 59.9 | 23.5% | 11.2× | 13 | +121.2% |
| 4 | Zhejiang Normal UniversityChina | 59.1 | 17.8% | 10.2× | 11 | +239.7% |
| 5 | Paderborn UniversityGermany | 58.5 | 27.2% | 15.9× | 9 | +160.8% |
| 6 | ETH ZurichSwitzerland | 58.3 | 37.0% | 6.1× | 16 | -24.9% |
| 7 | Princeton UniversityUnited States | 54.4 | 43.4% | 6.8× | 11 | -49.3% |
| 8 | University of California San DiegoUnited States | 51.8 | 25.3% | 6.4× | 21 | -11.8% |
| 9 | Chongqing University of Posts and TelecommunicationsChina | 49.8 | 11.2% | 9.4× | 11 | +293.7% |
| 10 | Weizmann Institute of ScienceIsrael | 49.5 | 22.7% | 17.2× | 10 | -37.6% |
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 Gene Regulatory Network Analysis research growing?
Output in 2018–2022 was 9% lower than in 2013–2017, peaking in 2013. The fastest-growing topics are Gene Regulatory Network Analysis.
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.