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Retinoids in leukemia and cellular processes

Retinoids in leukemia and cellular processes is a research topic within Molecular Biology. Science Explorer counts 33k research works in it since 1950. 15.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers explores the role of retinoic acid in various biological processes, including its involvement in acute promyelocytic leukemia, gene expression regulation, vitamin A metabolism, and embryonic development. It also discusses the interaction of retinoic acid with nuclear receptors such as RXR, the use of arsenic trioxide in treatment, and the potential for differentiation therapy.

  • Retinoic Acid
  • Acute Promyelocytic Leukemia
  • RXR
  • PML Nuclear Bodies
  • Arsenic Trioxide
  • Gene Expression Regulation
  • Vitamin A Metabolism
  • Nuclear Receptors
  • Differentiation Therapy
  • Embryonic Development
Research works
33k
fractional, since 1950
In the world top 10%
5k
per year above
Top-10% rate
15.1%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
-8%
the tick is no change

Which countries lead Retinoids in leukemia and cellular processes research?

By volume, China and the United States publish the most (847 and 658 works in 2022–2025).

By volume, 2022–2025

  1. 1 China 847 works
  2. 2 United States 658 works
  3. 3 India 205 works
  4. 4 Japan 131 works
  5. 5 Brazil 83 works
  6. 6 Germany 82 works
  7. 7 Italy 81 works
  8. 8 Türkiye 80 works
  9. 9 Iran 80 works
  10. 10 United Kingdom 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.

China: 36.4%United States: 28.3%India: 8.8%Japan: 5.6%6 others listed: 20.8%36%largest
China847 · 36.4%United States658 · 28.3%India205 · 8.8%Japan131 · 5.6%6 others listed483 · 20.8%

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

Which institutions lead Retinoids in leukemia and cellular processes research?

By volume in 2022–2025, The University of Texas MD Anderson Cancer Center publishes the most Retinoids in leukemia and cellular processes research, followed by Chinese Academy of Medical Sciences & Peking Union Medical College and Shanghai Jiao Tong University.

Who are the leading researchers in Retinoids in leukemia and cellular processes?

The most-cited researchers publishing on Retinoids in leukemia and cellular processes include Walter C. Willett, Amirhossein Sahebkar and Michael Karin.

  1. 1 Walter C. Willett United States 6.8k citations
  2. 2 Amirhossein Sahebkar Iran 5.6k citations
  3. 3 Michael Karin United States 4k citations
  4. 4 Hagop M. Kantarjian United States 4k citations

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

Where is Retinoids in leukemia and cellular processes research done?

The largest centres of Retinoids in leukemia and cellular processes research in 2022–2025 are Beijing (China), Shanghai (China), Guangzhou (China) and Hangzhou (China). Among places with at least 20 works in it, it is an unusually large share of all research in Houston.

Largest cities, 2022–2025

  1. 1 Beijing China 94 works
  2. 2 Shanghai China 67 works
  3. 3 Guangzhou China 52 works
  4. 4 Hangzhou China 43 works
  5. 5 Paris France 36 works
  6. 6 Houston United States 34 works
  7. 7 Wuhan China 33 works
  8. 8 Tokyo Japan 33 works
  9. 9 Nanjing China 31 works
  10. 10 London United Kingdom 31 works

Where it is the local speciality

  1. HoustonUS · 34.4 works4.5×
← less than its size predictsmore →

Location quotient: how much more of its research is in Retinoids in leukemia and cellular processes than the world average.

See Retinoids in leukemia and cellular processes on the map

Where is the best place to study Retinoids in leukemia and cellular processes?

Among universities, judged by research, Chinese Academy of Medical Sciences & Peking Union Medical College, Shanghai Jiao Tong University and Zhejiang 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.

0%20%40%mean 17.28%fractional works in this node (log) →share in the world top 10% →Chinese Academy of Medical Sciences & Peking Union Medical College: 16, 19.3%Shanghai Jiao Tong University: 11, 26.0%Zhejiang University: 9, 25.3%Case Western Reserve University: 9, 14.9%Central South University: 9, 29.4%Harbin Medical University: 10, 11.5%Sun Yat-sen University: 9, 22.6%University of Alabama at Birmingham: 8, 7.2%Guiyang Medical University: 9, 6.4%University of Washington: 8, 10.2%Shanghai Jiao Tong U…Zhejiang UniversityChinese Academy of M…Case Western Reserve…
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Chinese Academy of Medical Sciences & Peking Union Medical CollegeChina 60.319.3%5.4×16 +12.6%
2 Shanghai Jiao Tong UniversityChina 47.626.0%1.6×11 +4.5%
3 Zhejiang UniversityChina 44.625.3%1.5×9 +8.6%
4 Case Western Reserve UniversityUnited States 43.514.9%8.2×9 -38.0%
5 Central South UniversityChina 42.329.4%1.7×9 -15.1%
6 Harbin Medical UniversityChina 40.411.5%15.7×10 -46.1%
7 Sun Yat-sen UniversityChina 37.522.6%1.9×9 -11.9%
8 University of Alabama at BirminghamUnited States 32.77.2%5.5×8 +33.7%
9 Guiyang Medical UniversityChina 32.46.4%21.8×9 -43.1%
10 University of WashingtonUnited States 28.810.2%2.6×8 +0.9%

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 Retinoids in leukemia and cellular processes research growing?

Output in 2018–2022 was 8% lower than in 2013–2017, peaking in 2009.

19801990200020102020
grewheldshrank

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.