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Topic · Molecular Biology

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. 9.9% 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%
2.8k
per year above
Top-10% rate
9.9%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
-6%
the tick is no change
Largest producer
United States
33% of the 10 largest, 2022-now
Gene Regulatory Network Analysis

Which countries lead Gene Regulatory Network Analysis research?

By volume, the United States and China publish the most (1.2k and 979 works in 2022-now).

By volume, 2022-now

  1. 1 United States 1.2k works
  2. 2 China 979 works
  3. 3 Germany 267 works
  4. 4 United Kingdom 245 works
  5. 5 France 219 works
  6. 6 India 195 works
  7. 7 Italy 159 works
  8. 8 Japan 157 works
  9. 9 Spain 96 works
  10. 10 Canada 87 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: 33.1%China: 27.3%Germany: 7.4%United Kingdom: 6.8%6 others listed: 25.4%33%largest
United States1,188 · 33.1%China979 · 27.3%Germany267 · 7.4%United Kingdom245 · 6.8%6 others listed912 · 25.4%

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

Which institutions lead Gene Regulatory Network Analysis research?

By volume in 2022-now, Centre National de la Recherche Scientifique publishes the most Gene Regulatory Network Analysis research, followed by Chinese Academy of Sciences and Harvard University.

By volume, 2022-now

  1. 1 Centre National de la Recherche ScientifiqueFrance 76 works
  2. 2 Chinese Academy of SciencesChina 43 works
  3. 3 Harvard UniversityUnited States 36 works
  4. 4 Shandong Normal UniversityChina 31 works
  5. 5 Shandong UniversityChina 28 works
  6. 6 Max Planck SocietyGermany 26 works
  7. 7 University of OxfordUnited Kingdom 26 works
  8. 8 Russian Academy of SciencesRussia 24 works
  9. 9 Imperial College LondonUnited Kingdom 24 works
  10. 10 University of California San DiegoUnited States 23 works

Who are the leading researchers in Gene Regulatory Network Analysis?

The most-cited researchers publishing on Gene Regulatory Network Analysis include Eric S. Lander, Yoshua Bengio and Rob Knight.

  1. 1 Eric S. Lander United States 524k citations
  2. 2 Yoshua Bengio Canada 476k citations
  3. 3 Rob Knight United States 468k citations
  4. 4 Peer Bork Germany 396k citations
  5. 5 Robert John Tibshirani United States 396k citations
  6. 6 Guido Kroemer France 386k citations
  7. 7 Karl John Friston United Kingdom 310k citations
  8. 8 Matthias Mann Germany 308k citations
  9. 9 Trevor Hastie United States 301k citations
  10. 10 Todd R. Golub United States 283k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Gene Regulatory Network Analysis?

The most cited paper in Gene Regulatory Network Analysis is "Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks" (Paul T. Shannon, Andrew Markiel, Owen W. Ozier et al., 2003), with 55,788 citations. Next come "edgeR : a Bioconductor package for differential expression analysis of digital gene expression data" (45,449) and "Collective dynamics of ‘small-world’ networks" (43,707).

Most cited papers
#PaperReleasedCitations
1 Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks Paul T. Shannon, Andrew Markiel, Owen W. Ozier et al. · Genome Research Open access Nov 2003 55,788
2 edgeR : a Bioconductor package for differential expression analysis of digital gene expression data Mark D. Robinson, Davis James McCarthy, Gordon K. Smyth · Bioinformatics Open access 11 Nov 2009 45,449
3 Collective dynamics of ‘small-world’ networks Duncan J. Watts, Steven H. Strogatz · Nature Jun 1998 43,707
4 Complex networks: Structure and dynamics Stefano Boccaletti, Vito Latora, Yamir Moreno et al. · Physics Reports 11 Jan 2006 11,156
5 Enzymatic assembly of DNA molecules up to several hundred kilobases Daniel G. Gibson, Lei Young, Ray-Yuan Chuang et al. · Nature Methods 12 Apr 2009 11,139
All 99 most cited papers, with filters and sorting

Where is Gene Regulatory Network Analysis research done?

The largest centres of Gene Regulatory Network Analysis research in 2022-now are Beijing (China), Paris (France), Shanghai (China) and Jinan (China).

Largest cities, 2022-now

  1. 1 BeijingChina 132 works
  2. 2 ParisFrance 98 works
  3. 3 ShanghaiChina 74 works
  4. 4 JinanChina 69 works
  5. 5 LondonUnited Kingdom 66 works
  6. 6 TokyoJapan 57 works
  7. 7 NanjingChina 55 works
  8. 8 BostonUnited States 47 works
  9. 9 CambridgeUnited States 47 works
  10. 10 GuangzhouChina 45 works
See Gene Regulatory Network Analysis on the map

Where is the best place to study Gene Regulatory Network Analysis?

Among universities, judged by research, Harvard University, Princeton University and California Institute of Technology 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 20.86%fractional works in this field (log) →share of work in the world top 10% →Jiangnan UniversityPrinceton UniversityCalifornia Institute…Harvard University
above the meannear itbelow it

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.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Harvard UniversityUnited States 78.622.3%2.9×36 -33.4%
2Princeton UniversityUnited States 69.826.6%6.9×12 +53.7%
3California Institute of TechnologyUnited States 69.522.4%13.2×19 +11.2%
4Jiangnan UniversityChina 65.831.3%5.4×13 +36.6%
5Weizmann Institute of ScienceIsrael 65.612.8%19.2×11 +40.5%
6Zhejiang Normal UniversityChina 65.419.0%10.7×12 +22.4%
7Hebrew University of JerusalemIsrael 64.124.3%5.9×12 +27.3%
8Shandong UniversityChina 63.714.6%5.4×28 +42.1%
9University of California San DiegoUnited States 63.715.8%6.0×23 -7.9%
10ETH ZurichSwitzerland 63.019.5%7.4×20 -34.0%

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 Gene Regulatory Network Analysis, country by country

Is Gene Regulatory Network Analysis research growing?

Output in 2022-2025 was 6% lower than in 2018-2021, peaking in 2013.

still counting19801990200020102020
grewheldshrank

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 Gene Regulatory Network Analysis as a percentage of every work published that year, 0.018% in 2024.

still counting0.020%0.040%0.060%Gene Regulatory Network Analysis0.018% in 202519801990200020102020

Fractional works of Gene Regulatory Network Analysis 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.

still counting5%10%15%Gene Regulatory Network Analysis9.7% in 2025200020102020

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.

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