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NF-κB Signaling Pathways

NF-κB Signaling Pathways is a research topic within Cancer Research. Science Explorer counts 23k 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 explores the role of NF-?B signaling in inflammation, immunity, and cancer. It covers various aspects such as the regulation of NF-?B activity, the link between NF-?B and inflammatory diseases, the impact of NF-?B on cancer development and progression, and the crosstalk with other signaling pathways. The papers also discuss potential therapeutic strategies targeting the NF-?B pathway.

  • NF-?B
  • signaling
  • inflammation
  • cancer
  • immunity
  • ubiquitination
  • transcription factors
  • TNF-a
  • IKK
  • regulation
Research works
23k
fractional, since 1950
In the world top 10%
2.3k
per year above
Top-10% rate
9.9%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
-21%
the tick is no change
Largest producer
China
57% of the 10 largest, 2022-now

Which countries lead NF-κB Signaling Pathways research?

By volume, China and the United States publish the most (1.2k and 359 works in 2022-now).

By volume, 2022-now

  1. 1 China 1.2k works
  2. 2 United States 359 works
  3. 3 South Korea 119 works
  4. 4 Japan 103 works
  5. 5 India 95 works
  6. 6 Germany 85 works
  7. 7 United Kingdom 52 works
  8. 8 Italy 39 works
  9. 9 Türkiye 37 works
  10. 10 Canada 36 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: 57.1%United States: 16.6%South Korea: 5.5%Japan: 4.8%6 others listed: 15.9%57%largest
China1,233 · 57.1%United States359 · 16.6%South Korea119 · 5.5%Japan103 · 4.8%6 others listed344 · 15.9%

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

Which institutions lead NF-κB Signaling Pathways research?

By volume in 2022-now, Nanjing Medical University publishes the most NF-κB Signaling Pathways research, followed by Shanghai Jiao Tong University and Zhejiang University.

Who are the leading researchers in NF-κB Signaling Pathways?

The most-cited researchers publishing on NF-κB Signaling Pathways include Eric S. Lander, Mark J. Daly and Guido Kroemer.

  1. 1 Eric S. Lander United States 524k citations
  2. 2 Mark J. Daly United States 403k citations
  3. 3 Guido Kroemer France 386k citations
  4. 4 Bert Vogelstein United States 373k citations
  5. 5 Shizuo Akira Japan 342k citations
  6. 6 Jun Wang China 340k citations
  7. 7 Giuseppe Remuzzi Italy 328k citations
  8. 8 Matthias Mann Germany 308k citations
  9. 9 Robert A. Weinberg United States 301k citations
  10. 10 Richard A. Gibbs United States 292k 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 NF-κB Signaling Pathways?

The most cited paper in NF-κB Signaling Pathways is "NF-κB signaling in inflammation" (Ting Liu, Lingyun Zhang, Donghyun Joo et al., 2017), with 8,517 citations. Next come "Toll-Like Receptors" (6,179) and "Bcl-2 heterodimerizes in vivo with a conserved homolog, Bax, that accelerates programed cell death" (6,042).

Most cited papers
#PaperReleasedCitations
1 NF-κB signaling in inflammation Ting Liu, Lingyun Zhang, Donghyun Joo et al. · Signal Transduction and Targeted Therapy Open access 14 Jul 2017 8,517
2 Toll-Like Receptors Kiyoshi Takeda, Tsuneyasu Kaisho, Shizuo Akira · Annual Review of Immunology Review 3 Mar 2003 6,179
3 Bcl-2 heterodimerizes in vivo with a conserved homolog, Bax, that accelerates programed cell death Zoltán N. Oltval, Curt L. Milliman, Stanley J. Korsmeyer · Cell Aug 1993 6,042
4 THE NF-κB AND IκB PROTEINS: New Discoveries and Insights Albert S. Baldwin · Annual Review of Immunology Review Apr 1996 5,979
5 NF-κB AND REL PROTEINS: Evolutionarily Conserved Mediators of Immune Responses Sankar Ghosh, Michael J. May, Elizabeth B. Kopp · Annual Review of Immunology Review Apr 1998 5,209
All 100 most cited papers, with filters and sorting

Where is NF-κB Signaling Pathways research done?

The largest centres of NF-κB Signaling Pathways research in 2022-now are Beijing (China), Shanghai (China), Guangzhou (China) and Nanjing (China). Among places with at least 20 works in it, it is an unusually large share of all research in Wenzhou.

Largest cities, 2022-now

  1. 1 BeijingChina 98 works
  2. 2 ShanghaiChina 91 works
  3. 3 GuangzhouChina 79 works
  4. 4 NanjingChina 58 works
  5. 5 HangzhouChina 57 works
  6. 6 SeoulSouth Korea 47 works
  7. 7 WuhanChina 43 works
  8. 8 JinanChina 38 works
  9. 9 ChangshaChina 36 works
  10. 10 Xi'anChina 32 works

Where it is the local speciality

  1. WenzhouCN · 20.7 works9.2×
← less than its size predicts1×more →

Location quotient: how much more of its research is in NF-κB Signaling Pathways than the world average.

See NF-κB Signaling Pathways on the map

Where is the best place to study NF-κB Signaling Pathways?

Among universities, judged by research, Sun Yat-sen University, Zhejiang University and Chinese Academy of Medical Sciences & Peking Union Medical College 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%10%20%mean 15.3%fractional works in this field (log) →share of work in the world top 10% →Harvard UniversitySun Yat-sen UniversityZhejiang UniversityChinese Academy of M…
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
1Sun Yat-sen UniversityChina 63.920.7%4.4×21 -39.6%
2Zhejiang UniversityChina 61.515.5%3.8×23 -7.7%
3Chinese Academy of Medical Sciences & Peking Union Medical CollegeChina 60.514.4%7.5×18 +8.7%
4Harvard UniversityUnited States 59.023.6%1.6×12 -51.9%
5Chengdu University of Traditional Chinese MedicineChina 58.517.8%15.5×9 +65.6%
6Central South UniversityChina 57.919.1%4.0×17 -3.4%
7Nanjing Medical UniversityChina 57.39.0%12.7×25 -16.6%
8Fudan UniversityChina 55.611.8%4.8×17 +5.7%
9University of California San DiegoUnited States 54.69.7%4.6×10 -9.7%
10Shanghai Jiao Tong UniversityChina 54.011.4%3.6×23 -24.8%

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 NF-κB Signaling Pathways, country by country

Is NF-κB Signaling Pathways research growing?

Output in 2022-2025 was 21% lower than in 2018-2021, peaking in 2010.

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 NF-κB Signaling Pathways as a percentage of every work published that year, 0.0085% in 2024.

still counting0.020%0.040%0.060%NF-κB Signaling Pathways0.0095% in 202519801990200020102020

Fractional works of NF-κB Signaling Pathways 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%NF-κB Signaling Pathways10.2% 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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