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Topic · Molecular Biology

Gene expression and cancer classification

Gene expression and cancer classification is a research topic within Molecular Biology. Science Explorer counts 33k research works in it since 1950. 10.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the analysis of microarray data and gene expression profiling, covering topics such as normalization, differential expression, feature selection, machine learning applications, clustering methods, quality control, and bioinformatics tools. The papers discuss various techniques and methods for processing and interpreting gene expression data obtained from microarray experiments.

  • Microarray
  • Gene Expression
  • Data Analysis
  • Normalization
  • Differential Expression
  • Feature Selection
  • Machine Learning
  • Clustering
  • Quality Control
  • Bioinformatics
Research works
33k
fractional, since 1950
In the world top 10%
3.3k
per year above
Top-10% rate
10.0%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+7%
the tick is no change
Largest producer
United States
32% of the 10 largest, 2022-now
Gene expression and cancer classification

Which countries lead Gene expression and cancer classification research?

By volume, the United States and China publish the most (1.4k and 1.3k works in 2022-now).

By volume, 2022-now

  1. 1 United States 1.4k works
  2. 2 China 1.3k works
  3. 3 India 675 works
  4. 4 Germany 185 works
  5. 5 United Kingdom 173 works
  6. 6 Italy 136 works
  7. 7 France 121 works
  8. 8 Canada 121 works
  9. 9 Japan 118 works
  10. 10 South Korea 101 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: 32.0%China: 29.7%India: 15.9%Germany: 4.4%6 others listed: 18.1%32%largest
United States1,358 · 32.0%China1,260 · 29.7%India675 · 15.9%Germany185 · 4.4%6 others listed769 · 18.1%

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

Which institutions lead Gene expression and cancer classification research?

By volume in 2022-now, Harvard University publishes the most Gene expression and cancer classification research, followed by University of North Carolina at Chapel Hill and Chinese Academy of Sciences.

By volume, 2022-now

  1. 1 Harvard UniversityUnited States 55 works
  2. 2 University of North Carolina at Chapel HillUnited States 51 works
  3. 3 Chinese Academy of SciencesChina 47 works
  4. 4 Centre National de la Recherche ScientifiqueFrance 34 works
  5. 5 National Institutes of HealthUnited States 27 works
  6. 6 Central South UniversityChina 22 works
  7. 7 Qufu Normal UniversityChina 22 works
  8. 8 University of MichiganUnited States 22 works
  9. 9 Shanghai Jiao Tong UniversityChina 21 works
  10. 10 Yale UniversityUnited States 21 works

Who are the leading researchers in Gene expression and cancer classification?

The most-cited researchers publishing on Gene expression and cancer classification 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 George Davey Smith United Kingdom 435k citations
  5. 5 Richard M. Durbin United Kingdom 410k citations
  6. 6 Mark J. Daly United States 403k citations
  7. 7 Stacey L. Gabriel United States 402k citations
  8. 8 Peer Bork Germany 396k citations
  9. 9 Robert John Tibshirani United States 396k citations
  10. 10 Bert Vogelstein United States 373k 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 expression and cancer classification?

The most cited paper in Gene expression and cancer classification is "Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method" (Kenneth J. Livak, Thomas D. Schmittgen, 2001), with 184,956 citations. Next come "Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles" (58,060) and "edgeR : a Bioconductor package for differential expression analysis of digital gene expression data" (45,449).

Most cited papers
#PaperReleasedCitations
1 Analysis of Relative Gene Expression Data Using Real-Time Quantitative PCR and the 2−ΔΔCT Method Kenneth J. Livak, Thomas D. Schmittgen · Methods Dec 2001 184,956
2 Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles Aravind N. Subramanian, Pablo Tamayo, Vamsi Krishna Mootha et al. · Proceedings of the National Academy of Sciences Open access 30 Sep 2005 58,060
3 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
4 limma powers differential expression analyses for RNA-sequencing and microarray studies Matthew E. Ritchie, Belinda Phipson, Di Wu et al. · Nucleic Acids Research Open access 20 Jan 2015 44,530
5 clusterProfiler: an R Package for Comparing Biological Themes Among Gene Clusters Guangchuang Yu, Li-Gen Wang, Yanyan Han et al. · OMICS A Journal of Integrative Biology Open access 28 Mar 2012 39,704
All 100 most cited papers, with filters and sorting

Where is Gene expression and cancer classification research done?

The largest centres of Gene expression and cancer classification research in 2022-now are Beijing (China), Shanghai (China), Guangzhou (China) and Chennai (India). Among places with at least 20 works in it, it is an unusually large share of all research in Qufu, Chapel Hill and Bhubaneswar.

Largest cities, 2022-now

  1. 1 BeijingChina 174 works
  2. 2 ShanghaiChina 97 works
  3. 3 GuangzhouChina 67 works
  4. 4 ChennaiIndia 66 works
  5. 5 New YorkUnited States 58 works
  6. 6 Xi'anChina 53 works
  7. 7 Chapel HillUnited States 51 works
  8. 8 ChangshaChina 51 works
  9. 9 SeoulSouth Korea 51 works
  10. 10 ParisFrance 49 works

Where it is the local speciality

  1. QufuCN · 22.3 works21×
  2. Chapel HillUS · 50.9 works5.1×
  3. BhubaneswarIN · 29.1 works4.8×
  4. New HavenUS · 22.6 works3.6×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Gene expression and cancer classification than the world average.

See Gene expression and cancer classification on the map

Where is the best place to study Gene expression and cancer classification?

Among universities, judged by research, Harvard University, Stanford University and Johns Hopkins 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%10%20%mean 16.15%fractional works in this field (log) →share of work in the world top 10% →Stanford UniversityPeking UniversityHarvard UniversityJohns Hopkins Univer…
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 81.517.7%3.6×55 +8.5%
2Stanford UniversityUnited States 62.220.4%2.8×20 -27.7%
3Johns Hopkins UniversityUnited States 59.814.6%2.7×20 +14.9%
4Peking UniversityChina 54.619.2%1.7×17 +27.7%
5University of WashingtonUnited States 53.910.5%2.6×14 +47.4%
6University of MichiganUnited States 53.712.1%3.0×22 +4.3%
7Vellore Institute of Technology UniversityIndia 53.016.6%3.7×18 +43.0%
8Heidelberg UniversityGermany 52.118.8%2.8×10 +25.6%
9Karolinska InstitutetSweden 51.714.6%3.8×10 +30.3%
10University of Chinese Academy of SciencesChina 50.817.0%1.6×13 +68.3%

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 expression and cancer classification, country by country

Is Gene expression and cancer classification research growing?

Output in 2022-2025 was 7% higher than in 2018-2021, peaking in 2008. The fastest-growing topics are Gene expression and cancer classification.

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 expression and cancer classification as a percentage of every work published that year, 0.024% in 2024.

still counting0.025%0.050%0.075%Gene expression and cancer classification0.023% in 202519801990200020102020

Fractional works of Gene expression and cancer classification 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 expression and cancer classification10.5% 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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